Technical risk assessment techniques in Mineral Resource

Technical risk assessment techniques in Mineral Resource
University of Pretoria etd – McGill, J E (2005)
Technical risk assessment techniques in Mineral Resource
Management with special reference to the junior and small-scale
mining sectors.
Jeannette Elizabeth McGill
Submitted in partial fulfilment of the requirements for the degree M.Sc. (Earth
Science Management and Practice) in the Faculty of Natural and Agricultural
University of Pretoria
May 2005
University of Pretoria etd – McGill, J E (2005)
LIST OF ABBREVIATIONS........................................................................................4
LIST OF FIGURES .......................................................................................................6
LIST OF TABLES .........................................................................................................7
INTRODUCTION .................................................................................................8
Objectives of the study...................................................................................8
Defining junior and small-scale mining.........................................................9
Defining the concept of risk.........................................................................11
THE SOUTH AFRICAN MINING SECTOR SINCE 1994 ...............................13
The SAMREC code .....................................................................................27
Corporate reporting of resource risk ............................................................32
MRM and the business model......................................................................34
RISK MANAGEMENT.......................................................................................42
The risk management cycle .........................................................................42
Risk identification within the mining environment .....................................44
Risk quantification/analysis techniques .......................................................56
Tools for managing MRM risk ....................................................................72
Risk control techniques................................................................................85
CONCLUSION AND RECOMMENDATIONS ................................................90
REFERENCES ............................................................................................................93
Appendix A: Application of matrix-based risk classification................................104
Appendix B: Geological modelling as a method of risk reduction........................110
Appendix C: Application of the Turnbull Process.................................................115
Appendix D: Application of a risk control technique............................................117
University of Pretoria etd – McGill, J E (2005)
Title of treatise:
Technical risk assessment techniques in Mineral Resource
Management with special reference to the junior and smallscale mining sectors
Name of author:
JE McGill
Name of study leader: Prof H Theart
Faculty of Natural and Agricultural Sciences
University of Pretoria
May 2005
The junior and small-scale mining sectors in South Africa play an important role in
the livelihoods of numerous communities. Mining is an opportunity, in the post-1994
democratic era, for many individuals to obtain access to much required empowerment
and socio-economic development. These sectors are, however, not without numerous
characteristics that pose problems for operators, legislators, and other role-players.
Mining is inherently risky, with operators experiencing numerous difficulties
throughout the life of mine.
This critical analysis provides understanding relating to the junior and small-scale
mining sectors of South Africa, as well as how mineral resource management issues
impact these sectors. The different phases within the risk management cycle are
described together with key techniques available to reduce the associated risks. The
applicability of these techniques for use in the junior and small-scale mining sectors is
highlighted. Opportunity does exist for junior and small-scale prospects and
operations to include such techniques in either the search for funding or monthly
planning and functioning.
It is, therefore, the risk management cycle and how it currently applies to a mineral
resource suitable for exploitation by the junior and small-scale mining sectors that are
the core focus. No management process can create additional value in the ground, but
various available mechanisms can go a long way to quantifying the inherent risk that
exists, highlighting the need to manage the risks and hopefully allowing the
entrepreneur access to the intrinsic opportunities of the emerging mining sector in
South Africa.
University of Pretoria etd – McGill, J E (2005)
Applications for Computers in Mining
African Rainbow Minerals
Artisanal Small-scale mining
Australian Institute of Mining and Metallurgy
Anglovaal Minerals
Black Economic Empowerment
Business Risk Period
Communities and small-scale mining
Council for Geosciences
Canadian Institute of Mining
Council of Mining and Metallurgical Institutions
Competent Persons Report
Council for Scientific and Industrial Research
Discounted Cash Flow
Department of Minerals and Energy
Democratic Republic of Congo
Debt Service Cover Ratio
Department of Trade and Industry
Economic Value Add
Gross Domestic Product
Graphic Mining Solutions International
Historically Disadvantaged South African
Industrial Development Corporation
International Labour Organisation
International Monetary Fund
Institute of Mining and Metallurgy
Independent Peer Review
Internal Rate of Return
Joint Ore Reserve Committee
Johannesburg Securities Exchange
University of Pretoria etd – McGill, J E (2005)
Long Inclined Borehole
Life of Mine
Mineral Economics Society
Mineral and Petroleum Resources Development Act 28 of 2002
Mineral resource management
Mineral Resources Forum (of UNCTAD)
Mine Qualifications Authority
New African Mining Fund
Net Present Value
National Steering Committee of Service Providers to the SSM Sector
New York Stock Exchange
Reverse Circulation (drilling)
Relative Density
Research and Development
Run of Mine
Rock Quality Designation
South African Institute of Mining and Metallurgy
South African Mineral Resources Committee
Standard Deviation
Specific Gravity
Small Mining Unit
Small-scale mining
United Nations
United Nations Conference on Technology and Development
United Nations Development Program
United States Dollar
Value Area Curve
South African Rand
University of Pretoria etd – McGill, J E (2005)
Figure 1: Components of the minerals sector showing where most of the historical
industry research focus has been directed............................................................10
Figure 2: Key concepts of the SAMREC code (SAMREC, 2000) ..............................29
Figure 3: Schematic representation of the relationship between mineral resource and
reserves (Carey, 2002) .........................................................................................29
Figure 4: Schematic diagram representing the mine value chain and its associated
inputs (Crecy, 2002).............................................................................................35
Figure 5: Schematic diagram of the relationship between the mine value chain and
levels of governance (Carey, 2002) .....................................................................36
Figure 6: EVA - The linkage between short and long-term value addition (Macfarlane,
2000) ....................................................................................................................39
Figure 7: Schematic diagram showing the relationship between how risks are handled
depending on the expected rate of return for a project (Gitman, 1994)...............47
Figure 8: How bank financing of projects changes according to the overall stage of a
project as well as the relationship between risk and reward (Benning, 2002).....49
Figure 9: Calculation of DSCR....................................................................................49
Figure 10: Example of an application of a decision tree (figures are illustrative).......62
Figure 11: Comparison of the stepping pump concentrator (foreground) and sluice
boxes (background) for small-scale gold recovery. .............................................63
Figure 12: Example of a sensitivity analysis undertaken on a potential junior-scale
operation in Limpopo...........................................................................................64
Figure 13: Graphical representation of the result of a conditional simulation process,
for 25 series. The range of possible grades is clearly shown (Carey, 2002)........68
Figure 14: Impact of increased drilling on the distribution of project NPV (Sullivan,
2003) ....................................................................................................................70
Figure 15: A typical value-area curve (VAC)..............................................................75
Figure 16: Representation of the basal reef horizon pick in a 3D cube – Tshepong
Mine .....................................................................................................................81
Figure 17: Regression plot as a comparison of kriged block estimates for December
1999 and March 2000 on a mine. The original estimated values (December 1999)
are compared to re-estimated samples on the basis of stope sampling. As the
scatter plot reveals a good correlation (slope approaching 1) the estimation
process is deemed accurate (AngloGold Limited, 2001b)...................................84
Figure 18: Illustration of the Tau Lekoa 3D model showing fault, dyke and reef
surfaces ..............................................................................................................112
Figure 19: Basal reef structural changes due to geological modelling on Tshepong
Mine. The top diagram represents the structure model in June 2000, while the
diagram below represents the structure in June 2001. Dramatic changes in
geological structure are revealed by colour coding mining levels.....................114
Figure 20: Example of the modelled reef (blue) and fault surfaces (red) of Tshepong
Mine, with borehole information included ........................................................114
University of Pretoria etd – McGill, J E (2005)
Table 1: Characteristics of the South African Mining Sector......................................11
Table 2: Guidelines for a small-scale mine definition (Peake, 1998a) ........................20
Table 3: Current DME classification (Sihlali, pers comm) .........................................20
Table 4: Small-scale mining at global and regional levels (UNDP, 2004)..................21
Table 5: Estimate of the small-scale miner population by province (Peake, 1998a)...23
Table 6: Application of risk categorisation and SAMREC classification ...................31
Table 7: MRM framework and related key objectives (MacFarlane, 2004)................41
Table 8: Summary of risk areas that impact on the MRM function and possible
analysis techniques...............................................................................................44
Table 9: Risk parameters related to common cash flow parameters (Simonsen and
Perry, 1999)..........................................................................................................45
Table 10: Elements of country risk (Smith, 2003).......................................................51
Table 11: Typical MRM activities with the corresponding technique and associated
data type. ..............................................................................................................53
Table 12: Example of MRM risks relevant to the junior and small-scale mining
sectors ..................................................................................................................57
Table 13: Matrix for determination of a mining method for a potential travertine
deposit (McGill, 2003).........................................................................................60
Table 14: Steps involved in the conditional simulation process (Snowden, 2002) .....69
Table 15: Summary of discount rates (%) in concept and practice (Smith, 2003) ......74
Table 16: Summary table setting out the applicability of risk management techniques
to the South African junior and small-scale mining sectors ................................88
Table 17: Three main areas of risk to the LIB drilling programme...........................105
Table 18: Probability/impact matrix used to assess risks of a LIB drilling programme
Table 19: The three main areas of risk to the LIB drilling programme and the
corresponding assessment result, where red is high risk, green is moderate risk
and blue is low risk ............................................................................................106
Table 20: Risks ranked as high ..................................................................................107
Table 21: Key headline risk concerns as identified by AngloGold Ashanti in 2001.115
Table 22: Factors with greatest risk for AngloGold’s South African operations in 2001
University of Pretoria etd – McGill, J E (2005)
Objectives of the study
The research question addressed in this study may be phrased as: How do participants
in the junior and small-scale mining sectors identify and control technical risk within
the Mineral Resource Management arena?
Mineral Resource Management (MRM) considers the mine-based disciplines of
survey, evaluation, geology, and planning as a single entity rather than as discrete
functional domains, and has a critical role to play within successful and profitable
mining. MRM-related issues impact significantly on all stages of the mining cycle.
Often, MRM-related decisions are difficult to quantify but remain the basis for all
mining operations, never the less.
In subsequent sections some of the influential changes that have occurred since the
launch of the “new South Africa” in 1994 will be discussed and this discussion
provides the platform for a detailed introduction to the junior and small-scale mining
sectors and some of its inherent characteristics. The concept of mineral resource
management is introduced and the importance of SAMREC and other corporate
compliance is shown as particularly relevant to the junior and small-scale mining
sectors. The treatise then looks at MRM-related risk issues in particular, and exposes
some of the quantifiable and probabilistic techniques available to quantify such issues.
Risk concerns need to be addressed for exploration programmes, mining projects, as
well as for mining operations. This treatise defines the concept of risk across the
mining sector and identifies and describes the key aspects of the risk management
cycle, which combines the critical aspects of risk identification, analysis and control.
The applicability of various elements of the risk management cycle to the junior and
small-scale mining sectors is commented upon.
The junior and small-scale mining sectors have emerged to be a potentially important
role-player within the South African mining sector and this work sets out to address
University of Pretoria etd – McGill, J E (2005)
certain implications of mineral resource-related risk for this sector. MRM is a concept
developed by large multinationals, but is often not holistically applied to the junior
and small-scale sectors. For successful mining outcomes, the ability to combine and
holistically appraise the impact of risk, especially within the MRM environment, is
critical. The ability to tailor solutions for the small and junior sectors is paramount to
the success of these sectors.
It is important to note that this treatise will concentrate on technical risk as it relates to
mineral resource risk issues, and the related impact on the junior and small scale
mining sectors of South Africa. It is implicitly understood in this industry that various
types of risks prevailing in the mining industry interact, and that no project can
progress without a holistic assessment of all the particular risks affecting the potential
operation. For example, mineral resource risk could be well defined and be considered
favourable but other risk domains, for example, country risk, financial risk, or market
related-risk could be overriding factors that limit the possibilities of subsequent
development. Therefore, for completeness, various risk types are presented although
briefly. A detailed assessment of these other risk areas and related interactions is
beyond the scope of this treatise.
Defining junior and small-scale mining
This treatise deals with the junior and small-scale mining sectors, as they pertain to
the South African minerals and mining sector. Unfortunately, various other miningintense countries have similar terms, with slightly different associated definitions. The
gradation of operation size is provided in Figure 1, with the position of the junior and
small-scale mining sectors.
University of Pretoria etd – McGill, J E (2005)
Major local
Historical focus
Figure 1: Components of the minerals sector showing where most of the historical industry
research focus has been directed
In the Australian and Canadian context junior mining companies primarily identify,
explore, and delineate new mineral deposits. Once this is achieved, the entire or only a
portion of the prospect is sold to a major or multinational company for mine
development (Cooper, 2004). In South Africa, however, an entirely different approach
is taken to “junior mining”. South African junior mines are role-players in the
emerging mining sector, a sector that is characterised by the development of BEE. In
the current dispensation such juniors often acquire marginal deposits, as outliers to
large well-understand deposits mined by the majors (AngloGold Ashanti, Harmony,
Goldfields, to name a few). Examples of current junior mining companies include
Sebilo Resources, Retsibogile Mining and Nozala Diamonds.
Small-scale mining has been defined in a variety of ways (see Section 3). The term
“small-scale mining” is often interchanged with “artisanal mining” or even “artisanal
small-scale mining”. Artisanal and small-scale mining encompasses all mining
operations that, by virtue of their size and overall turnover etc, are categorised as
small. Small-scale mining also sometimes includes illegal miners or the West African,
South American “garimpero’s” or “galamsey”. The illegal sector is a high priority to
be eliminated in most countries, but this is not without difficulty. In the South African
context the boundaries between each category are not distinct, hence the confusion
that is often expressed. This concept of small-scale mining is fully defined in Section
University of Pretoria etd – McGill, J E (2005)
Defining the concept of risk
The Oxford Complete Wordfinder (1993) defines risk as “a chance or possibility of
danger, loss, injury or other adverse consequences”, while risk within an operational
environment is defined by Kerzner (2001) as “a measure of the probability and
consequence of not achieving a defined goal”. The King Report on Corporate
Governance (Institute of Directors, 2002; Terblanche, 2002) defines risk as “uncertain
future events which could influence the achievement of a company’s objectives. The
Institute of Directors (2002) states that these “could include strategic, operational,
financial and compliance objectives” and that “some risks must be taken in pursuing
opportunity, but a company should be protected against avoidable losses”.
Conversely, opportunity can be viewed as the opportunity or likelihood of doing
better than a specified goal. Achieving an outcome, therefore, represents the most
likely scenario in terms of the interaction of risk and opportunity factors evaluated.
Specific to the mining sector, Agricola (1556), in his famous treatise on mining, De
Re Metallica, refers to the need for understanding the geology of a particular deposit
for successful mining, while Krige in 1955 also developed many aspects of mining
risk in his work on risk analysis in mining ventures. The mining industry in South
Africa exhibits some unique characteristics when compared with other industrial
sectors. These factors (Table 1) result in a very interesting and difficult sector,
responsible for underpinning the entire South African economy.
Table 1: Characteristics of the South African Mining Sector
Typical Characteristics
High risk versus reward
Capital intensive procurement
Price taker
Cyclical profits and losses
Remote locations
Finite life of a non renewable resource
Reclamation and rehabilitation liabilities
State ownership of the mineral resource
University of Pretoria etd – McGill, J E (2005)
The Warren Study of 1991 in Glacken (2002) assessed the percentage of -over- versus
underestimation of various parameters in Australian gold mining operations. These
parameters included capex, opex, gold recovery and grade estimation. Grade was
shown to have been 95% overestimated in the study, which equated to a value, at that
time, of AUS $95 million. Croll (1999) undertook a study of 11 projects ranging over
some 30 years to assess how well various factors (mineral reserves, tonnages, grade,
capex and opex) were estimated. The results revealed that three factors carried the
greatest risk of accurate determination. These factors are:
Grade estimation of the mineral reserve;
The valuation methodology; and
Forecasting the metal price.
The first two of these factors are considered in this treatise.
University of Pretoria etd – McGill, J E (2005)
Prior to the democratisation of South Africa in 1994, junior and small-scale mining
had been largely ignored or regarded as a troublesome activity that did not contribute
towards the attainment of national objectives. The practice was largely confined to the
alluvial diamond sector. Furthermore, an exclusionary legislative framework
restricted access to minerals rights and active participation in the minerals sector to a
small privileged proportion of the country’s population and greatly favoured the
entrenched mining houses. With the establishment of a new government, a realisation
occurred that junior and small-scale mining could be a vehicle for creation of
economic activity in remote communities, a mechanism of job creation, and a basis
for skills development that could be transferable to other sectors of the economy
(McGill, 2004).
Government, and particularly the DME, has therefore sought to actively encourage the
growth of small-scale mining ventures. It is one of the key pillars of DME policy to
promote small-scale mining, and the DME has been instrumental in establishing
several initiatives, partly through the national science and technology system, which
can stimulate responsible small-scale mining activity. The intent is to cover the entire
range of smaller-scale operations, from truly small-scale mining currently in the
second economy, to what, in South Africa, would be termed “junior mining
companies”, i.e. those fledgling mining companies that are one of the keys to
attainment of the goal of broad-based participation in the minerals sector.
It was recognised in the development of the new framework for governing the
minerals sector that the rich national heritage of minerals should be accessible for the
benefit of all South Africans without regard to ethnic background or gender (Cawood,
2003). A significant process of reform in the legislative and governance framework
has therefore been undertaken, and this has culminated in the passing of various new
laws. An inclusive, participative and consultative approach was followed in redrafting the framework.
A cornerstone of the new framework is the broad-based socio-economic charter for
the South African mining and minerals industry, commonly referred to as the “Mining
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Charter” (Cawood, 2003). It was recently subscribed to with commitment from all of
the major stakeholders in the mining and minerals sector. These stakeholders include
state, labour, the major mining companies, and organisations representing smaller and
developing mines and mining companies.
The first objective of the Charter (Cawood, 2003) is to promote equitable access to the
nation's mineral resources for all the people of South Africa. The Charter is founded
on seven pillars of social and economic development, these being:
Human resource development;
Employment equity;
Community upliftment;
Housing and living conditions;
Beneficiation; and
While the Mining Charter is subscribed to voluntarily as an appropriate route for the
development of the sector, it is also backed up in law by Act no 28 of 2002, the
Mineral and Petroleum Resources Development Act, which provides for the
conversion of old-order minerals rights to new-order rights. Under this Act, mining
companies will be required to report, using a scorecard against defined performance
targets, in each of the seven pillars as a pre-requisite for renewal of mining rights.
A fundamental shift in philosophy under the new legislation is the move to ownership
of minerals rights by the state, with prospecting and mining rights being granted to
organisations that comply with specified conditions, and certain preferences being
granted to HDSAs and small enterprises. The state may provide assistance as required
to HDSAs to support them in conducting prospecting or mining operations. The
Mining Charter commits the state to providing institutional support and other
measures for supporting HDSA companies in exploration and prospecting endeavours
(Government Gazette, 2004). Various means of financial support exist to fund
feasibility studies, the development of mining plans, and skills development.
University of Pretoria etd – McGill, J E (2005)
A specific provision of the new governance framework is that the granting of a
mining right is required to develop opportunities for historically disadvantaged
persons, including women, to enter the mineral and petroleum industries and to
benefit from the exploitation of the nation’s mineral and petroleum resources. The
new Minerals Act also provides for mining permits to be issued for small-scale (<1.5
ha), short-duration (<2 yrs) mining operations under an administratively less
burdensome protocol (Section 4 (27) MPRDA, 2002). This will make it easier for
small-scale mining operations to become incorporated into the formal sector of the
economy, but will nevertheless increase the extent of regulation of the small scale
mining sector in the national interests, particularly relating to the protection of the
environment and the securement of decent, safe and healthy employment conditions
for the workforce in such operations.
A further provision of the new legislation is that preference is to be given to local
communities in the granting of prospecting and mining rights (MPRDA, 2002). The
rights of indigenous peoples whose lives and communities are affected by mining
activities to share in the financial returns have been upheld in landmark rulings, such
as those in favour of the indigenous population in the Richtersveld that have been
allocated 10% of the Alexcor Mine (Nxumalo, 2003). The mining companies are also
committed to supporting socio-economic development in labour-sending areas in
terms of the Charter and associated scorecard requirements. (This case is again
currently in court.)
The change in philosophy also provides for the “use it or lose it” principle, under
which major players can no longer retain rights to prospect or mine indefinitely
without actively and responsibly exploiting the minerals resource. Specific time
periods are prescribed for which a prospecting or mining company may hold rights
before advancing a mining project through its natural phases. This development in
law will also provide more equitable access to minerals deposits to smaller roleplayers, emerging companies, and small-scale operations (MPRDA, 2002).
While many portions of the governance framework of the minerals sector are not
directly relevant to small-scale mining itself, the new requirements subscribed to by
the established players should have major ramifications for the emerging smaller
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players in the minerals sector, as well as for those currently engaged in the minerals
sector through the second economy. In South Africa, as well as other developing
nations, the concept of ‘two economies’ has been developed to consider both the
dominant and competitive ‘first economy’ as well as the marginalised ‘second
economy’. The second economy is characterised by isolated practices that do not
contribute to the first and global economies. For a single economy to prevail targeted
initiatives are required that overcome poverty and unemployment (SARPN, 2004).
Some of the major mining companies are responding to this challenge by identifying
portions of the minerals resources over which they have mining rights that they cannot
mine effectively and that would be suitable for exploitation by smaller operators. (An
example of such a “take off agreement” exists in the Northern Cape where marginal
Sishen iron-ore deposits are mined by local BEE miners, but with a fixed sales (ore
supply) contract to the Sishen Mine (Noetstaller et al., 2004, Sihlali, pers comm). The
mining companies provide technical assistance and access to markets for such smaller
operators. These initiatives vary significantly in size, but include some projects at a
scale where they could be regarded as poverty-reduction initiatives at micro scale.
From industry’s side, there is also agreement to assist HDSA companies in securing
finance to fund participation through equity in an amount of R100 billion within the
first five years. Examples of existing funds are the Anglo-Khula fund, the Bakubung
initiative, as well as the New African Mining Fund. In addition, government provides
further funding via entities or organisations like the IDC, the National Empowerment
Fund (administered by the DTI) and the National Steering Committee of Services
Providers to the small-scale mining sector (administered by the DME).
The success of such support initiatives is continually in the spotlight (Sihlali, pers
comm).It is a common complaint that governments burden small-scale operators with
unrealistic regulatory requirements and often fail in adequately providing the much
needed aid, training, and support (Hilson, 2002).
Transformation within the South African mining industry context has resulted in
numerous landmark transactions such as the establishment of African Rainbow
Fields/Mvelaphanda deal. All these transactions have been based on asset valuations,
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internal feasibility studies, and competent persons report, all of which fall within the
ambit of the MRM practitioner. Joint venture arrangements are also reliant on
reconciliations of tonnage, grade and product, also within the MRM domain.
In summary, the new governance framework for the granting of prospecting and
minerals rights is fundamentally friendlier towards the needs of junior and small-scale
operators. The objectives of the new government policy, supported by the newly
developed legislative framework, are to attract greater participation by individuals
from historically disadvantaged backgrounds into responsible mining activities that
are appropriate to national interests. In addition, this policy should facilitate
integration, through legitimising, of illicit mining operations into the regulated formal
sector of the economy. Enhanced levels of partnership between big and small business
will develop during the journey towards sustainable community development centred
on mining operations.
There remain major challenges, many of these in common with other sectors of the
economy, in supporting the transition of small-scale mining for poverty reduction
from the second economy into the formal economy of the country, where it can
contribute optimally to the national benefit. Integration remains an essential objective
to ensure that the nation’s mineral wealth can be transformed optimally into other
forms of capital that will support the sustainable development of communities.
Appropriate regulation of small-scale mining is vital to avoid the erosion of value in
the mineral resources or even the creation of significant net liabilities due to
irresponsible mining activity. In terms of the current legal and administrative
framework, inadequate provision is made for assisting the small-scale mining sector
in the identification, quantification and management of mineral resource-related risk.
University of Pretoria etd – McGill, J E (2005)
Small-scale mining is an essential activity in many developing countries, as it
provides an important source of livelihood, particularly in regions where economic
alternatives are critically limited. This form of mining is a livelihood strategy adopted
primarily in rural areas. In many cases, mining represents the most promising, if not
the only, income opportunity available (MMSD, 2002; Hilson, 2002; McGill, 2004).
Many governments consider this sector as a source of problems that relate to noncompliance with mine health and safety laws as well as environmental, labour and tax
laws (among others). In the eyes of critics, the sector is seen as a remnant of an
antiquated way of doing things, swept away by the forces of corporate capitalism
(Danielson, 2003). The concept of artisinal and small-scale mining has been debated
at length in the literature (Peake, 1998a; ILO, 1999; Drechsler, 2001). In addition, it
has been revealed that many stakeholders have a definition of small-scale mining,
which may suit a specific requirement, or viewpoint (Drechsler, 2001, p 147):
To poverty stricken and hungry people in both rural and urban areas, smallscale mining is a "God-given answer to their woes";
To individuals involved in gold and semi-precious minerals (e.g. emeralds and
diamonds), small-scale mining is the "fast track process to their earthly
riches"; and
To independent observers, small-scale mining is the "greatest environmental
Most formal definitions attempt to categorise mines in terms of one or more physical
criteria. These criteria may include: mineral type; annual production (tons mined or
minerals produced); the value of commodity produced or capital invested; or the
number of people employed (Peake, 1998b). In effect, nations develop their own
definitions as to what constitutes smallness depending upon their mixes of
sociological, geographical, financial, and technical factors. An example of an
individual country and an organisations efforts to define small-scale and small-scale
University of Pretoria etd – McGill, J E (2005)
mining are set and the problems, constraints and omissions in the definitions are
Ghana: “Small-scale mining refers to operations of individual Ghanaians or
organised groups of Ghanaians (4 -8) or cooperatives (>10), which are entirely
financed by Ghanaian resources at a certain time limit, and carried out on a
full-time basis using simple equipment and tools” (MRF, 2005, p1).
United Nations: “Small-scale mining is any single unit mining operation
having an annual production of unprocessed materials of 50 000 tons or less as
measured at the entrance of the mine” (MRF, 2005, p1).
In this treatise, within the South African context, small-scale mining is defined as
small operations operating at the lower end of the cost curve with limited employees.
For the purposes of this treatise and to limit overlap and confusion this definition will
also include artisanal operations, which are often transitory and/or illegal. In addition,
this definition implicitly includes holders of a “mining permit” as defined in the
Minerals and Petroleum Resources Development Act, 2002. A mining permit “may
only be issued if:
a) The mineral in question can be mined optimally within a period of two
years; and
b) The mining area in question does not exceed 1.5 hectares in extent (Section
4(27)(1), MPRDA (2002)).
A breakdown of operation size is given in Table 2 below, where this treatise applies in
effect to all the categories, as many South African juniors are in fact medium-scale
operations. Unfortunately the matter is further complicated by a second definition
(Table 3), which is applied by the DME and based on the following (Sihlali, pers
University of Pretoria etd – McGill, J E (2005)
Table 2: Guidelines for a small-scale mine definition (Peake, 1998a)
Capex (R’000)
Annual Tonnage
< 2000
Micro Small
6 – 20
5 – 99
2000 – 9999
Very small
21 – 49
100 – 7999
10 000 – 99 999
50 – 99
8000 – 24999
100 000 – 249 999
Medium scale
100 - 999
> 25000
> 250 000
Table 3: Current DME classification (Sihlali, pers comm)
Turnover (R)
Gross Assets (R)
150 000
100 000
Very Small
6 – 20
3 million
1.8 million
21 – 49
7.5 million
4.5 million
30 million
18 million
It must be stressed that each subdivision should not be viewed as an isolated cut-off.
Rather, an entire size spectrum exists with definite overlap between the individual
categories. In addition, often these category names are applied very loosely in the
press and in discussion. One person’s existing formal small mine may be another’s
aspiration with regard to a large operation. The true impact of junior and small-scale
mining is associated with development nodes that have been instigated through
mining activities. The numbers of individuals relying indirectly on small-scale mining
operations are therefore even greater.
Small-scale mining is a poverty-driven activity, most often practised by the poorest of
the population sector. Often the practice is migratory in nature (Ghose, 2003). This is
particularly true in the South African context in the alluvial diamond sector. When
undertaken as a subsistence activity, growth opportunities will not exist and escape
from the cycle of poverty is considered unlikely (Peake, 1998b). Literacy levels of
small-scale miners are low and often mining is conducted in below-standard safety,
environmental and occupational health conditions. It is commonly associated with
informal, undercapitalised and under-equipped operations. It does, however, have the
potential to enrich and economically empower disadvantaged communities
(Drechsler, 2001). The UNDP believes that to improve the livelihoods of the small-
University of Pretoria etd – McGill, J E (2005)
scale miners, alternative livelihood opportunities need to be developed and the entire
sector needs to be formalised. For this reason, an in depth knowledge of the
underlying resource/reserve that will underpin such developments is essential.
An important realisation is that some ore bodies may not lend themselves to smallscale mining practices. This lack of suitability could be attributed to depth,
mineralogical complexity, or mode of extraction required. The South African mining
sector cannot afford to lose the big players and the two sectors (large and small)
actually need to develop side by side. Often junior and small-scale mining entrants
require money “now” and considering long-term impacts, cash flows and risks to
MRM related decisions are not seen as important.
Approximately six million people and some 30 million dependants are involved
(UNDP, 2004) in small-scale mining activities worldwide, and roughly half of these
are in China (Table 4). 90% of India’s mines are operated on a small-scale (Ghose,
2003). Recent research by the ILO suggests that throughout the world small-scale
mining involves in the order of 13 million people directly, mainly in developing
countries, and that it affects the livelihoods of a further 80 – 100 million (Hinton et
al., 2003). It is estimated than in Southern Africa alone some 1.5 million people are
directly employed by this sector (Drechsler, 2001).
Table 4: Small-scale mining at global and regional levels (UNDP, 2004)
Employment (‘000’s)
Burkino Faso
Gold, Tin
Central African Republic
Gold, Diamonds
Gold, Diamonds
Gold, Diamonds
University of Pretoria etd – McGill, J E (2005)
Sierra Leone
Gold, Diamonds
Gold, Chromite
Total Africa
Iron, Coal, Tin, Tungsten
Iron, Coal, Tin, Borates
Gold, Tin
Gold, Chromite, Coal
Total Asia
Latin America
Lead, Gold, Sulphur
Total Latin America
In South Africa, provinces with relatively high levels of small-scale mining activity
are the Northern Cape, NorthWest, Mpumalanga, and KwaZulu-Natal. Table 5
(below) was compiled in 1998 from a variety of sources. It must be remembered that
operating conditions are constantly fluctuating and these numbers can only be
regarded as an indication of the situation. Through the current formalisation process
for small-scale miners at the DME a more up-to-date indication may be possible,
especially after the promulgation of the MPRDA (2002).
Many people are involved in the mineral sector, even at a rudimentary level, and the
key to successful, sustainable operations is a crucial understanding of mineral
resource issues. Certain commodities are more ideally suited to small-scale extraction
than others. Examples include: alluvial diamonds, aggregates (dolerite and granite),
University of Pretoria etd – McGill, J E (2005)
clay, and surface coal. Beneficiation is, of course, crucial for downstream value
addition and suitable avenues include clay bricks, cement bricks, and pottery. Smallscale mining does have the ability to produce minerals from deposits that are not
economic to mine on a larger scale. This is largely due to the economies of scale
associated with these smaller endeavours, that may not be as capital intensive as
larger operations. Therefore, junior and small-scale mining are not sectors which
should continue to be ignored as they have been.
Table 5: Estimate of the small-scale miner population by province (Peake, 1998a)
Province NCape NWest M’langa KZN Limpopo Gauteng WCape ECape
It is very difficult to obtain conclusive figures pertaining to the contribution of the
junior and small-scale mining sectors to GDP, or figures on the exports from the
small-scale mining sector, as it is largely unregulated. Most often, production is from
“hand-to-mouth”. The underlying need is to link this second economy to the primary
economy, which will enhance economic growth and result in such economic
contribution data being more readily available. Studies have revealed that the small
mines category contributes 1.1% to mining sector employment and 2.5% to sector
revenue (Noetstaller et al., 2004). A more current figure relating to small-scale
diamond miners considers some 1000 miners, with about 25,000 people being
employed by the sector as a whole. The purchasing power of the community is
estimated to be in the order of R7.7 billion per annum (Coetzee, 2004).
Mining is a very technical and costly endeavour. As certain initiatives require only
limited start-up capital, prolonged financial support is often neglected (Hilson, 2002).
If such operations are going to perform throughout a reasonable LOM then increased
access to funding mechanisms will result in the ability to upgrade equipment and
improve efficiencies. Due to the small-scale mining permit only being valid for two
years, the level of funding available to operators is limited. Not many mechanisms are
Diggers = Registered diamond diggers
University of Pretoria etd – McGill, J E (2005)
available for potential operators as a result of the inherent risk in investing in mines
with shorter lifecycles. This ultimately means that less capital is available for
technical assistance in the form of contractors or consultants. Often, only the legal
requirements, such as survey, are covered by the junior operators. This results in most
aspects of MRM, which could sustain an operation over a longer period, being
For the small-scale sector the function of MRM resides with the state as the owner of
the minerals. The state should thus develop the sector to the level where the MRM
responsibility could be passed on to the operators. In addition, it could be the function
of the small-scale mining directorate within the DME to support MRM-related
capacity-building initiatives. This treatise describes many of the risk techniques
relating to different parts of the risk management cycle and provides evidence to
support the potential application of the methods to this sector.
University of Pretoria etd – McGill, J E (2005)
Harrison (2000, p1) states that MRM refers to “professionally (managing) the
exploitation of mineral resources or reserves to meet company objectives”. MRM is
therefore an integrated activity, including the application of sound management
principles that maximise the value of the mineral asset, in order to grow shareholder
wealth (Macfarlane, 2000). In recent times a change in organisation structure to
embrace this holistic approach has resulted in a more process-driven and value-added
approach to MRM. MRM considers the mine-based disciplines of survey, evaluation,
geology and planning as a holistic entity rather than separate functional domains. On
smaller operations the need for such disciplines is no less important. Functionally,
most of the MRM-related decisions become the responsibility of a single mineral
resource practitioner, rather than an entire department.
How, therefore, is risk management undertaken within MRM? The concept of risk
management is no longer the sole domain of the health and safety department,
corporate office, or legislative enforcement. In the past few years it has become more
apparent that the mineral resource manager (practitioner) needs to be responsible in
dealing with the risk to the overall business risk that is grounded in the orebody
(Macfarlane, 2004). To be effective, MRM requires a system that will identify,
quantify, and manage the risks associated with the orebody. To be able to do this the
person responsible for MRM needs to possess the requisite skills and competencies to
undertake quantitative risk management and to report accordingly.
Internationally, MRM is a concept that is not considered in such detail as in South
Africa. Internet research on the topic provides links to mainly government sites that
have information relating to mineral rights ownership, deeds offices, and
environmental issues. This “type” of MRM-related work is, however, commonly
carried out by the mining engineering department. Certain overseas operations are
managed by South African multinational mining houses. Therefore, it is the opinion
of the author that through effective MRM and related successes the approach will take
root in many more operations. The main difference between current MRM and
previous operational techniques is that the current approach considers MRM as a
“seamless” approach, with total integration being the key to the process, while
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traditional international practice is to add important issues of optimisation onto
already established mining engineering structures.
Macfarlane (2000) suggests that besides the integration of survey, evaluation, geology
and planning functionalities a further integration with certain financial functionalities
will allow MRM to maximise shareholder wealth. In reality, this linkage is between
strategic and operational planning, where overriding corporate goals are translated
into operational mining plans, which can achieve the required growth.
In the bigger picture MRM has a role to play within corporate governance. Corporate
governance is important as it provides the guidelines and platform for companies to
operate internally and interact externally (PriceWaterhouseCoopers, 2003). As the
Institute of Directors (2002, p 18) states: “Corporate governance, is essentially about
leadership”. The extent to which companies adopt and demonstrate good principles of
corporate governance will impact on investment decisions (OECD, 1999). This
premise is particularly relevant for junior operators within the South African context
who often seek financing. The ability to display sound corporate governance practices
will go a long way in securing funding. MRM corporate governance issues relate, in
particular, to the following (Macfarlane, 2004):
Diligent management of the mineral assets (i.e. to add value and reduce risk);
Compliance with public reporting requirements (see section 4.1);
The management of risks associated with the mineral asset; and
Contribution to operating within a context of sustainable development.
The SAMREC code of South Africa underpins all mineral resources issues and is the
code that all reporting and corporate governance within the minerals sector must
adhere to. The true challenge involves how this code could be applied to the small and
junior mining sectors. Section 4.1 provides the background and describes features of
this code in more detail.
University of Pretoria etd – McGill, J E (2005)
The SAMREC code
Globalisation of the mining industry has resulted in the need for public (standard)
reporting codes in the major countries associated with mining related capital funding.
In October 1997 the CMMI’s International Definitions Group met in Denver, Colorado,
and reached a provisional agreement (the Denver Accord) on definitions of mineral
resources and mineral reserves. This agreement went a long way to providing the
platform of requirements stipulated by the NYSE. Concurrently, and since 1992, the
United Nations Economic Commission for Europe has also been developing an
international framework classification for mineral resources and mineral reserves.
Agreement was reached to incorporate the CMMI standard reporting definitions for
mineral resources and mineral reserves into the UN Framework Classification, thus
giving truly international status to the CMMI definitions (SAMREC, 2000). It is this
platform that the various individual country-specific codes are built on.
The first such code to be established was the JORC code of Australia in 1999. This was
followed by the SAMREC Code of South Africa in 2000, the CIM Code of Canada in
2000 and the European Reporting Code in 2001 (Mullins et al., 2003). This section
describes in more detail the background and critical issues contained within the South
African SAMREC Code. The definitions in the SAMREC Code are consistent with
those agreed at the Denver Accord by the CMMI participants. This section also
highlights the impact the code has had on small and junior scale operators.
The compilation of the South African code began in 1998. SAMREC was tasked by
the SAIMM to compile a South African reporting code for reporting mineral
resources and mineral reserves (the SAMREC Code). The code was finalised after a
long consultative process with key role-players including government institutions, law
societies and the AusIMM Joint Ore Reserve Committee (JORC). The code is
therefore endorsed both locally and overseas. The SAMREC code is the required
minimum standard for public reporting of exploration results, mineral resources, and
mineral reserves in South Africa (Camisani–Calzolari, 2000). The code has officially
been adopted by the JSE as a portion of requirements for new resource sector listings.
University of Pretoria etd – McGill, J E (2005)
Even though many of the small-scale operators will never list on the JSE and the
juniors may only strive for a listing, the need to attract funding from various available
sources, such as banks and aid agencies/funds, makes striving for SAMREC
compliance prudent.
The code requires the proper disclosure of all factors likely to affect the accuracy of
the resource and reserve estimates made. Such information becomes part of the
competent person’s report where the “competent person” is someone who has a
minimum of five years experience relevant to the evaluation of resources and reserves
for the style of mineralisation and type of deposit under consideration. In addition, the
person must be a member of a statutory body recognised by SAMREC such that
conduct contrary to the code of ethics can be dealt with. Similar requirements are also
stipulated in other codes like JORC and “The Reporting Code” representative of the
IMM, as well as of London’s and Ireland’s Geological societies (IMM, 2001). In
Canada, the CIM’s terminology merely refers to a “qualified person” but the same
requirements are stipulated (Goscoe, 2001).
The relationship between the key concepts of the SAMREC Code is shown in Figure
2. From greenfields exploration mineral resource estimates are made and are
classified according to the corresponding level of confidence in the estimate. Through
the application of various “modifying factors”, the mineral resource categories
displaying the highest confidence (indicated and measured) can be “converted” to
actual mineable reserves. This progression is schematically provided in Figure 3.
University of Pretoria etd – McGill, J E (2005)
In cre a sin g
le ve l o f
R e p o rte d a s in situ
R e p o rte d a s
g e o scie n tific
m in e ra lisa tio n
m in e a b le p ro d u ctio n
kn o w le d g e
e s tim a te s
e stim a te s
co n fid e n ce
C o n sid e ra tio n o f m in in g , m e ta llu rg ica l, e co n o m ic, m a rke tin g , le g a l,
e n viro n m e n ta l, s o cia l a n d g o v e rn m e n ta l fa cto rs
(th e 'm o d ifyin g fa c to rs')
Figure 2: Key concepts of the SAMREC code (SAMREC, 2000)
Geological modelling
Metallurgy etc
Grade estimation
Geological and grade model
Pit optimisation
Mine design / costing &
Figure 3: Schematic representation of the relationship between mineral resource and reserves
(Carey, 2002)
University of Pretoria etd – McGill, J E (2005)
The level of confidence in ore grade values becomes very important and underpins the
classification of resources and reserves. Geostatistics, therefore, provides the only
basis for estimates with the lowest expected error variance and is free of biases.
SAMREC also requires estimates of tonnages and grades for resources and reserves
and the provision of confidence levels (SAMREC, 2000). Confidence should be
expressed in terms of both accuracy (the absence of biases) and precision (limits of
error). The confidence in a project will depend largely on the lower confidence limit
for the grade (Camisani–Calzolari, 2000). Where statistical and/or geological
uncertainty exists the categorisation is downgraded accordingly. Risk can therefore be
reflected by the likelihood of having certain grade values, within appropriate impact
limits of the predicted grades:
Low risk
90% probability of quarterly grade within 10% of prediction
Medium risk
80% probability of annual grade within 20% of prediction
High Risk
70% probability of global grade within 30% of prediction
This incorporation of low, medium, and high risk “categories” is, however, not a
stated requirement of SAMREC. An illustration of various possible conditions and the
resultant classification, based on the categories described above (Dewar, 2001) is
provided in Table 6.
Although the estimates of mineral resources are not dependent on the economics of
exploiting the deposit, uncertainties in their estimation (risk) impact directly on the
mineral reserves that are derived from them. To understand the concept of risk fully a
critical distinction between uncertainty and variability is required.
Natural variability is a fundamental characteristic within a variable and cannot be
reduced with further study. (An example of this is the nugget effect of diamond and
other precious mineral deposits.) Uncertainty is created by lack of knowledge
regarding a particular system and can be decreased with further study and associated
University of Pretoria etd – McGill, J E (2005)
understanding (Glacken, 2002). Therefore, uncertainty needs to be reduced through
gaining of more information. This process will have an associated cost-benefit trade
off (e.g. the use of 3D seismics for data acquisition or not) and to quantify uncertainty
using available techniques, one which is conditional simulation (refer to Section
Table 6: Application of risk categorisation and SAMREC classification
Limited exploration data and only global Inferred mineral resource
Data permits some estimates on the spatial Indicated mineral resource
Provisional estimate on expected global Lower confidence limit – 15%
tonnages and grade above any cut-off are
Level of estimates is suitable for long-term
planning and feasibility studies.
Valuation of individual blocks of ore, SMU Measured mineral resources with modifying
(small mining unit) or larger. However, factors: probable reserves
smoothing effect occurs during kriging as a
result of limited data.
Lower confidence limit – 10%
Final selection and valuation of SMU blocks
Measured mineral resources with proven
Lower confidence limit – 5%
Smaller operations can often not meet the required density of data required for proper
resource/reserve classification due to the overriding costs in obtaining such data. They
therefore operate with much higher resource-risk profiles. Producing high ore grades
is obviously not as significant, risk wise, as intersected low grades and associated
discontinuities. Owing to the lack of background data it is very difficult to predict
accurate grade distributions. Risk reduction should be addressed as a continuous
process. Financial strength and associated grade trends during “good times” should be
used to reduce the risk regarding the mining of the remaining resources.
University of Pretoria etd – McGill, J E (2005)
Corporate reporting of resource risk
The ability to accurately identify and report mineral resource and technical riskrelated issues goes a long way to ensuring good standards of corporate governance. At
the forefront of corporate governance reporting standards is the Sarbanes-Oxley Act
of 2002 from the USA, as well as the King Report on Corporate Governance for
South Africa, 2002, which set directives for reporting on risk. The King Report of
2002 was a second version of the groundbreaking King Report of 1994, which
introduced the need for reporting of the triple-bottom line (Institute of Directors,
2002). This concept involved the reporting of all economic, environmental and social
aspects of a company’s activity. The Sarbanes-Oxley Act meant the “tightening of
(PriceWaterhouseCoopers, 2003).
A working group commissioned by the London Stock Exchange to address riskmanagement issues resulted in the Turnbull process. This approach has been adopted
as the process to follow by various listed South African companies, including
AngloGold Ashanti(Dewar, 2001). The first steps of the Turnbull process are to
identify “headline risk areas” and to define the business objectives in these key areas
(Appendix C). In other words, high-level business objectives are subdivided into
smaller and very specific success factors. Associated with this process is the
identification of key performance indicators that can be monitored (Hiles, 2005). Key
factors that may affect achieving company goals are then identified and evaluated
according to a numerical scale in terms of impact and probability of occurrence. This
aspect of the Turnbull process occurs in two steps: first without controls in place; and
then again with controls in place. Finally control, reporting, and monitoring systems
that are in place to manage the risks are documented.
In the process of this research various annual reports of the major role-players in the
South African mining industry were accessed so that a perspective could be obtained
on the reporting aspects of mineral resource and reserve related risk. In the
AngloGold annual report (2001a) no reference is made to mineral resource risk issues
but the report does clearly highlight the contingent of competent persons responsible
University of Pretoria etd – McGill, J E (2005)
for signing off the ore resource and reserve statements. Harmony (2002, p 24) states
that “gold reserve figures are estimates based on a number of assumptions and may
yield less gold under actual production conditions than (they) currently estimates”.
The report goes on to state that “the reserve estimates contained in the report should
not be interpreted as assurances of economic life of Harmony’s gold deposits or the
profitability of its future operations”. The competent person responsible for the South
African operations is also mentioned. AVMIN (2001) clearly describes the process
undertaken by the competent persons to evaluate the resources and reserves as well as
the gold price etc. No issues specific to potential MRM risk are highlighted. Placer
Dome Group (2001) sets out the competent person contingent together with the
variety of cut-off grades applied to their suite of deposits. Placer Dome Group
mentions that various potential projects exist in the pipe-line however warns investors
that in keeping with the corporations strategy of maximising returns on investment,
there is no guarantee that any of the projects will be developed.
The importance of good corporate governance and reporting techniques has evolved
from 2001/2002 to the current situation where Ernst and Young in South Africa
compiles an “excellence in corporate reporting” report, which surveys the annual
reports of South Africa’s Top 100 companies. Two mining companies (AngloGold
Ashanti and Impala Platinum) are listed in the top 10 places in the 2005 survey (Ernst
and Young, 2005). This is clear evidence for improved reporting of mineral resources
and reserves as a measure of improved cognisance of mineral resource management
issues. This shift in MRM reporting is particularly evident from the Goldfields
website where more information is available when compared to 2001/2002. Mineral
reserve and resource issues are collated into a separate document (Goldfields, 2004).
The objective for Impala Platinum when reporting resources and reserves is “to focus
attention on reporting reserves in a clear and credible manner (as) investors are buying
into the future cash flows related to those reserves and resources” (Business Day,
2005a). The company makes careful use of diagrams and maps to ensure the reader
understands these issues perfectly. The AngloGold Ashanti annual report “carefully
explains the business and lays out the risks that the company faces” (Business Day,
University of Pretoria etd – McGill, J E (2005)
While issues of corporate governance, Turnbull definitions and transparency are high
on the priority list of public companies most junior and small-scale operations are not
as conscientious. This fact should, however, not make them any more complacent in
these compliance issues. Juniors should especially practise high company standards as
a means to achieving overall growth. It is strongly recommended that individual mine
operators highlight risk areas in the business plans or mine works programmes.
MRM and the business model
Good MRM should embody a deeper understanding of the overall business objectives
of a company and/or operation, such that the overriding business objective of the
MRM function becomes “maximising shareholder wealth through effective utilisation
of the assets viz. the mineral resource” (Macfarlane, 2000). However, as previously
emphasised, the concept of MRM is very much the domain of large-scale operations.
In smaller operations, this role is often fulfilled by the geologist and/or outside
consultant, where/if such people can be afforded. MRM is not a discipline that should
be viewed as the prerogative of larger operations but as a practice that needs to be
applied to all operations within the entire minerals sector.
In terms of the sustainable development concept, good MRM requires a balance to be
achieved between complete exploitation of a deposit, irrespective of the financial
implications and the “rape and escape” attitude of picking the “eyes” out of a deposit.
Stakeholders, including the ultimate owners of the operation, the local community, as
well as the government all need to be convinced that the exploitation process is
beneficial to all. The same considerations also need to be applied by the junior and
small-scale operators, such that affected parties, authorities, investors, and
downstream buyers of beneficiated products know that these mines have also been
operated in a sustainable manner.
As alluded to in the introduction to this treatise, the mining business environment is
considered to be unique in that margins are narrow, operations are capital intensive,
ventures are costly, and risk levels are high. These features are even more apparent
University of Pretoria etd – McGill, J E (2005)
within the junior and small-scale mining sectors. Gitman (1994, p 225) reveals that
“return and risk are the key determinants of share price, which represents the wealth
of the owners”. It may then be interpreted that to achieve shareholder wealth,
improved value or profit maximisation, overriding risk should be kept at a minimum.
At the Denver World Gold Summit in 1999 Mr Cockerill of Goldfields International
stated that: “shareholders get value in two ways. They get value in terms of money
today and money tomorrow. Money today is clearly in the form of dividends and
money tomorrow is in the form of capital growth.” Careful MRM is therefore required
to optimally extract ore for maximising shareholder wealth. Within the small-scale
mining sector the ability to achieve optimal growth is even more difficult.
Mine value chain
Figure 4: Schematic diagram representing the mine value chain and its associated inputs (Crecy,
Prior to delineating the orebody for mining purposes it is the role of the exploration
geologist to identify the deposit through exploration and prospecting activities. MRM
considers the delineation of mineral resources and their conversion to mineral
reserves, as described in the previous section. According to the value chain concept
the mining company/operation may be modelled as a series of primary activities that
are responsible for the generation of value, together with a range of supporting
activities that do not directly generate value but support value generating activities.
The mine value chain concept establishes a continuum from MRM to production and
University of Pretoria etd – McGill, J E (2005)
finally processing aspects (Figure 4). Planning integration is required and, finally, the
quality control of the saleable product through to marketing and sales is ensured.
Macfarlane (2004) defines the mining value chain as representing sequential work
flow, as it relates to the mining process. Intrinsic to this “chain” is the feedback loop
to the orebody, which relates to the ability of the orebody to deliver now as well as in
the future.
The level of corporate involvement will also adjust during the different phases of the
project and mine value chain, as well as according to the overall monetary value of
the potential investment (Figure 5). BHP Billiton considers detailed review by a
customer selected board together with independent peer reviews, undertaken by a
variety of different committees, as an integral part of the investment approval process
(Mullins et al., 2003). This process assists in understanding all the risks associated
with individual investment opportunities.
Value Creation
Project Concept
Value Delivery
Involvement of IPR team
>US$M Peer reviews
by CSG
Decision to Invest
Independent Peer Reviews
Peer reviews by CSG
Customer Sector Board Decision
Board Submission & Decision
NB. Customer Sectors will
establish appropriate governance
ExCo Decision
Investment Review
Figure 5: Schematic diagram of the relationship between the mine value chain and levels of
governance (Carey, 2002)
University of Pretoria etd – McGill, J E (2005)
The mining value chain can therefore be used to identify critical MRM competencies.
These would include (MacFarlane, 2004):
The ability to integrate value chain activities and technical inputs;
The ability to interface with production and processing and to analyse variance
when it occurs;
The need to have a sufficient understanding of the other departments, to be
able to add value;
The assurance of technical quality; and
The development of competencies at lower levels so as to allow data
integration, information flow and action.
The mining value chain operates within the overall business environment. The generic
fundamental requirements of a mine-related business model are:
Both short-term and long-term value must be balanced;
Growth in shareholder value must be achieved;
A balance between revenue and available resources, which are not generating
revenues, needs to be achieved; and
Cash generated now must be put to work to generate wealth tomorrow
Unfortunately these requirements are often not formally adhered to by the junior and
small-scale operators. Small-scale mining has particular difficulties with subscribing
to such requirements because most operations emerge from impoverished
environments and are often managed by poorly skilled operators. The need to survive
for today overrides any call to save for tomorrow. It is therefore the challenge of the
government and technical assistants alike to instil the groundwork for such a shift in
attitude to enable smaller operations to continue to be sustainable into the future.
Short and long-term value
The interaction between long-term and short-term value within the mining company is
very relevant to the junior-scale operations whose aim it is to list on the JSE, or to be
University of Pretoria etd – McGill, J E (2005)
viewed on the “radar screen” of larger national operators. Components of short and
long-term value should be items that small-scale operators are encouraged to consider.
Typical components of short and long-term value are given below:
Short-term value:
The associated value of the resource and the reserve base, including the ability
of the operation to produce earnings from these assets in the short term;
The liquidity position of the operation;
The cost level of the operation;
The operational performance of the operation;
The level of free cash flow;
The ability to utilise opportunities that can add short term value; and
Flexibility in operation to switch to higher grade portions.
A measure of short-term performance, and a predictor of future performance, is
provided in the use of standard financial ratios. Values evident in balance sheets and
income statements are used to calculate the following typical ratios for listed
Earnings per share;
Price/earnings per share;
Cash flow per share; and
Net asset value per share.
Long-term value:
The relationship between the resource and the reserve base;
Optimal time-based utilisation of the mineral base to ensure a balance between
resource utilisation and profitability;
Long-term viability through commodity price fluctuations; and
Negating sterilisation induced through achieving short-term objectives.
University of Pretoria etd – McGill, J E (2005)
Long-term value is assessed through a discounted cash flow model (DCF)
incorporating concepts of Net Present Value (NPV), Rate of Return (IRR), growth
rate and payback period. (Refer to section 5.4.2.)
Linking short and long-term value:
The concept of Economic Value Add (EVA) balances short-term profitability with the
long-term objectives contained within the DCF analysis and feasibility study. It
measures the success of a company as the rate of cash generation (after interest, tax
and the cost of capital) compared to the use to which the cash has been put. This
concept is illustrated in Figure 6.
Return on Net
Economic value add (EVA)
Cash flow
Longer Term
Net Present
Value (NPV)
Dividends – shortterm value
Figure 6: EVA - The linkage between short and long-term value addition (Macfarlane, 2000)
EVA can be incorporated into the MRM arena in the follows ways:
The inherent value of a mining company is reflected in the balance sheet. This
value is based in terms of the overriding mineral asset and its valuation. This
valuation, by definition, incorporates the geological model, grade evaluation,
application of modifying factors and planning of extraction (the mine plan).
All of these are fundamental to effective MRM.
University of Pretoria etd – McGill, J E (2005)
Cost reductions can lower cut-off grades, which, according to MacFarlane
(2000), can increase the underlying ore body value. However, it can be argued
that if costs are cut, then profits would increase, benefiting the shareholders.
Therefore, careful consideration to ensure that such decisions are
economically viable is required before lowering cut-off grades.
An effective response, through efficient MRM, to changing external factors
such as variations in commodity price, must be adopted.
MRM Managers need to know which factors contained within a DCF can be
controlled and, therefore, where best value addition estimates can be achieved.
MRM for the junior and small-scale mining sectors
Macfarlane (2004) has provided a breakdown of what the MRM practitioner should
identify within the corporate MRM framework (Table 7). It should be emphasised that
the processes provided are cyclical and require constant feedback and evaluation
throughout the LOM.
In addition to the elements in Table 7, adaptability of the mining plan and product
spread to certain products (where the ore allows) is also important. Within the coal
sector, certain less quantifiable but important elements of MRM exist. Van Wyk
(2000, p 5) states “that the MRM practitioner has to (have) a deep understanding of
the colliery and any neighbouring areas”. Furthermore when market conditions
change or new markets develop the MRM practitioner needs to be proactive in the
inclusion of such aspects as the impact of new technology, associated impact on cutoff grades and reserve definition, So that the colliery product spread and mining plan
best suits the requirements of the market.
Finally, it is prudent for mining role-players, to establish where the MRM
functionality resides in junior and small-scale operations. Ultimately, the strategic
responsibility lies with the board of directors or the mine owner. At an operational
level MRM competency is often provided by a consultant to the operation, or an
independent consultancy firm. Obviously the proviso is that the operation can afford
such expenses. For many of the smaller operations this is not possible, resulting in
issues of MRM largely being ignored, to the detriment of the deposit and future of the
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mine. One suggestion is that annual MRM sessions are facilitated by the South
African science councils and/or the Chamber of Mines and other interested
stakeholders to address these issues in a structured way, for the benefit of all junior
and small-scale mines.
Table 7: MRM framework and related key objectives (MacFarlane, 2004)
Application of international and national protocols and codes applicable to MRM
A risk mitigation strategy document
A risk register
An area risk plan which relates specific area risks to the planning horizons, the
extraction sequence, and the geological models
A set of company specific protocols for the following areas:
Resource and reserve estimation
Feasibility studies
Mine design (codes of practice)
Metal accounting
A holistic audit protocol
A set of controls on key risk areas and key variables
An audit schedule
An audit review and progress document
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The risk management cycle
An example of where the decision to ignore certain critical risks resulted in complete
failure presents in the case of the Manville Corporation, a role player in the asbestos
industry. When this company deliberately chose to ignore the health risks associated
with asbestos they subsequently became responsible to fund a personal injury
settlement worth USD 150 million in cash, USD 1. 6 million in bonds, 80% of its
stock, and 20% of the company profits since 1992, as long as there are claims to settle
(Oosthuizen et al., 1998). If a sound risk management process had been adopted such
a liability may have been avoided. Nowadays, there are safe ways to use asbestos,
where there are no other alternatives, but the safe use of asbestos came 50 years too
late to save this sector of the minerals sector.
Dealing with risk requires that risk management be viewed as part of a dynamic,
competitive process rather then just a static management activity or, as in the example
above, something that is completely ignored. There are three distinct aspects to
successful risk management. These include (Toll, 1994):
Risk identification: both internal and external to the operation;
Risk analysis: using any of a variety of techniques; and
Risk response: based on the identification and analysis a response to the risk
can be formulated prior to the problem occurring.
All business development initiatives involve elements of risk. The appropriate
identification and management of these risks should be seen as the key to effective
and sustainable growth, if effectively managed. Risk identification, as the first phase
of the risk management cycle, can be completed by consulting objective (past
experience) and/or subjective (knowledgeable experts) sources (Kerzner, 2001).
Various different risks can also be identified during the life-cycle phases of a project
or operation. Risk management assists with the improvement in decision making as
the entire cycle/process (risk identification, assessment, and response/management)
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contributes towards a greater understanding of all risks and potential opportunities and
losses. The risk management process is as much about identifying opportunities as it
is about avoiding loss exposure. The risk management cycle as applied to mineral
reserves and resources is discussed in subsequent paragraphs.
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Risk identification within the mining environment
This statement by Mr A. Levitt (Chairperson of the US Securities Exchange
Commission) is particularly relevant for the mining sector: “The average company
today is a complex enterprise engulfed by rapid technological change and fierce
global competition. You have to assess exposure to risk on an ever changing
landscape.” The underlying importance of a mining organisation accurately
identifying all risks is obvious. This section deals with describing the principal types
of risks present within the mining environment, irrespective of scale of operation. An
introduction to this section is provided in Table 8.
Table 8: Summary of risk areas that impact on the MRM function and possible analysis
Risk Area
Methods of Analyses
Business Risk
High level of economic uncertainty exists
Cash flow models (scenario planning)
business Discounted Cash Flow models
Sensitivity analysis
Monte Carlo Simulation
Natural Risk
Geological uncertainty
Geotechnical risk assessment
More difficult to quantify and dependable on Conditional simulation
of Other techniques based on repeatability and
variance of sampling results.
From the financial institution viewpoint (Simonsen and Perry, 1999) the key to
lending money for projects is not simply to be a source of funding, but to determine
which projects have risk profiles that will provide adequate assurance for the
repayment of the loans according to plan. Unfortunately, the plight of most smallscale operators is that the majority of financing needs are viewed as highly risky by
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banking institutions. The impact of project risk can be equated to cash flow
parameters, as provided in Table 9.
Table 9: Risk parameters related to common cash flow parameters (Simonsen and Perry, 1999).
Cash flow parameters
Risk parameters
Commodity recovered
Revenue received
Gross revenue
Royalties, fees
Operating costs
Interest expense
Net after tax
Capital costs
Loan repayment
Debt/Equity Ratio
Foreign exchange
The cyclical behaviour associated with the expansion, extraction and duration phases
of commodity prices impacts on the volatility of the sector. A basic management tool
for commodity cycle management has been cost reduction (Simonsen and Perry,
1999). The key to identifying mineral resource-related risks is to be aware of the
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typical commodity market characteristics, as well as potential impacts on price risk.
Price risk can be attributed to the following factors:
Commodity price fluctuations over time;
Market share variances;
Demand inconsistencies; and
Variability in quality of the sales product.
As most mining operations are, in fact, operating within a much larger environment
the concept of business risk period (BRP) may be a more appropriate consideration
(SRK, 2001). BRPs will be distinctive throughout the time of the project or operation
and will, therefore, impact on the risking of capital accordingly. The BRP
encompasses the following factors:
New discoveries that create competitive changes in the market;
The time taken for new mines to be brought into production;
Changes in technology of geological, metallurgical and mining applications;
The position on the world producer cost curve of the operation; and
Pay-back period requirements, which would include political risk.
In any mining venture it is possible to categorise the risk environment that the
investor is willing to allow. These risk preference behaviours are shown in Figure 7.
As risk increases (along the x-axis) the risk-indifferent venture will require no change
to the return. The risk-averse sector will expect proportionally higher rates of return
for increased risk. Because this approach considers risk “bad”, higher returns are
expected in compensation for taking the greater risk. For the risk-seeking portion the
required return may actually decrease for a given risk. Companies are willing to
sacrifice some returns in order that they can take higher risks. In practice, one tends to
only take on the risks one feels comfortable with (Gitman, 1994). The opportunity to
invest in a risk-seeking project may be viewed favourably as a company either has
information or expertise that would result in reducing the risk exposure or,
alternatively, the initial cost of investing in such a project is low, and value may be
added to the project that exceeds the investment required to the reduce the risk.
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Risk averse
Risk indifferent
Risk seeking
Figure 7: Schematic diagram showing the relationship between how risks are handled depending
on the expected rate of return for a project (Gitman, 1994).
Beside mineral resource-related risk areas various other risk areas exist within the
mining sector. Turnbull identifies only four main areas of risk: business, financial,
compliance, and operational (Hiles, 2001). These, and certain other risk types, are
briefly described here to provide necessary background to this section of the treatise.
Management risk
Any mining-related project or aspect of operation, irrespective of scale, requires
careful management techniques. Management positions are often viewed as high
profile and challenging, with equivalent financial reward in the offering. Certain
downside risks (Kerzner, 2001) are not always apparent at the outset of the initiative
but could pose a significant threat to the expected outcomes if they are not fully
assessed. Work hours are often long and involved, and research shows that most
family relationships could be at risk at same time. Mining ventures have longer
lifecycles than other business ventures and will therefore take longer to produce
successes and failures. Quick successes are few. Success in the junior and small-scale
mining sectors will come through experience obtained by managing similar operations
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effectively. This management risk needs to be adequately addressed so that overall
goals are still achieved.
Financial risk
Mining is known to be very risky. This is largely due to the long planning horizon, the
project and/or LOM duration, the large amount of capital that must be invested, and
the financial risks of the markets. Risk is usually incorporated into the investment
decision by adjusting the discount rate within a DCF model. (Refer to section 5.4.2.)
Companies generally place risk categories on investments (Briers, 2002). Other DCF
considerations include the capex and opex requirements and need to be estimated for
particular operating periods. The accuracy of these estimates is therefore critical to the
overall outcome of the DCF model.
Studies have shown that ranges of costs estimated within feasibility studies can vary
between -5 to +15% (Nell and Burks, 1999).This variation is overcome within the
Bateman approach by using @Risk software plus applying a Monte Carlo simulation
to calculate the value of the mean deviation. The end result is an output range and
associated distribution curve for the cost estimates. Unfortunately, as a result of time
limitations such investigations for the junior and small-scale sectors are not often
The need for the formulation of an accurate DCF model is shown in how bank
involvement increases during the life of a project (Figure 8 ). It is possible to move a
project down the curve using the correct financial structuring (Benning, 2002). The basis
for any analysis in any of the categories shown in Figure 8 remains the discounted cash
flow model.
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Corporate Lending
Project Finance
Venture Capital
Increased bank
Operations with
smooth multiple cash
Figure 8: How bank financing of projects changes according to the overall stage of a project as
well as the relationship between risk and reward (Benning, 2002)
Often banks assess financial risk in the form of guideline ratios, where grade and
tonnages of reserves play a key role (Cole-Barker and Bower, 1998). One of the key
ratios is the Debt Service Cover Ratio (DSCR), which is the ratio between cash
available (usually annually) for debt repayment and the loan repayments plus interest
(Figure 9).
DSCR = Net Cash flow before debt servicing
Loan repayment + interest
= 1.5 minimum
Figure 9: Calculation of DSCR
As junior and small-scale operators require the same pre-feasibility, feasibility
documentation etc. as larger operations, the financial requirements also hold true for
this scale of operations too. Unfortunately the reality currently, in terms of the authors
personal experience, is that potential role-players often find the requirements both
onerous to fulfil and difficult to finance. This results in a “chicken and egg”
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phenomenon where the lack of funding means no feasibility documents can be
prepared. The lack of feasibility documentation means that banks are not prepared to
carry the risk of securing funding or guaranteeing loans.
Additional constraints result from certain industry rules. For example, the “Bankers
Rule” (Smith, 1997, p 48) states that “from a financier’s point of view mineable
reserves (cash flow) should be twice as large as the reserves (capital cost) to be mined
during the loan repayment period”. Other related economic “rules of thumb” state that
“the cash flow should pay the capital back in two years” and that a “minimum sevenyear life of mine” should exist (Smith, 1997, p 48). It is immediately obvious that the
ability of the majority of deposits, that junior and small-scale operators are
considering investing in, will not pass these “rules of thumb”. Junior miners may be in
the position to consider a portfolio of deposits that collectively contribute to a more
sustainable approach to extraction. It may be prudent for small-scale operations to
consider mineral terrains, e.g. the alluvial diamond sector, in the same regional
manner. Within the current dispensation, to support emerging role-players, certain
legislative and/or financial aspects may be deemed non-inhibitory so as to allow the
required development of the sector within South Africa. Once again, the overriding
proviso is that definite reserves exist.
Country risk
Country risk includes the following elements: political, geographic, economic, and
social. An expansion of each of these is given in Table 10. Many companies generate
their own risk assessment profiles of countries and/or companies in certain countries
(Simonsen and Perry, 1999). A risk profile can, however, not be better than a predefined envelope. For example, South Africa has a moderate risk profile (A-;
according to Standard and Poor’s, (2005)), so a specific project within South Africa
should not have a better risk rating. As will be demonstrated later, country risk is
normally included in the discount rate applied in a discount cash flow.
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Table 10: Elements of country risk (Smith, 2003)
Government stability
Foreign policy
Environmental policies and legislation (EIA,EMP)
Land claims
Currency stability
Foreign exchange policies
Ethnic influences
Literacy rate
Risk profiles can be generated by companies too, as companies tend to take much
higher risks than independent bodies. The negotiating of the “fairest” contract
between host government and the investing company is suggested as a means of
minimising risks. Most banking institutes issue credit ratings on the basis of short and
long-term outlooks. Such tables are available e.g. Standard and Poor’s. Where
financial institutions decide they cannot absorb political risk then the only recourse is
to access government-sponsored export-credit agencies, or the World Bank or funds
like the IMF.
Operational risk
A variety of potential risks exists in any mining operation. These diverse risks include
(but are not limited to): the application of a suitable mining method to enhance
optimal recovery; process performance from extraction through to final product
production; the application of an optimal schedule duration; staff and management
experience and expertise (related to the particular deposit and mining method); the
application of new or proven technology to enhance productivity; and, finally risks
associated with the incorrect scaling regarding exploitation and markets. Operational
risks are particularly relevant to the junior and small-scale mines. A relatively low
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level of technical competence exists. The need for capacity building and skills transfer
to improve this is important. Many junior-scale mines often enter into technical
operating agreements with partner companies. An example would be where the new
owner of a dolerite quarry engages with a contract mining company to perform the
technical function but is at the same time, contracted to provide much required skills
Technical risk
Mining is very technical industry. Technical risk can relate to any of the technical
requirements within mining. Technical risk will be prevalent in all decisions relating
to mining, rock engineering, engineering, metallurgy etc. In an attempt to identify a
unit of measurement for technical risk, acceptability criteria such as “time it takes for
failure” or “number of fatalities” may be considered. Most often, risk is also
calibrated in financial terms (Raftery, 1994).
Financial institutions rely on experts for assessing the technical aspects of all prefeasibility and feasibility-level studies. Technical aspects of MRM risk will be dealt
with in far more detail in subsequent sections of this treatise. However, in such
assessments the project initiator’s capability and experience are noted, especially in
relation to projects of a similar nature (Chicken, 1994). This accountability is
particularly important in relation to the CPR requirement within the SAMREC Code
(MRM and the business model). Often, where there is no hard quantitative data on
which to base decisions, recourse has to be taken to the qualitative opinions of
Resource risk
One specific area of technical risk is resource-related risk. Worth and Haystead, in
Glacken (2002, p 25) provide a particularly accurate assessment of the importance of
understanding resource-related risk:
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“The assessment of ore reserves is the most important point of any
technical evaluation. Errors in the project reserve estimate derived
from optimistic characterisation of grade continuity or the incorrect
application of calculation methodology are usually fatal. Money and
time can generally fix errors made in the estimation of certain
operating parameters. Money cannot create ore that was not put in
place by providence.”
There are a number of ways that resource risk can be assessed, both subjectively and
quantitatively. Resource modelling depends on subjective interpretation of measured
data. It is, therefore, very difficult to quantify the risk associated with this technique.
Resource estimation, however, is based on a series of best estimates from geological,
engineering and economic data. Therefore the ability exists to conduct a quantitative
resource risk assessment on this information.
Resource estimation inherently contains uncertainty, but the measurement of the
probabilities (expressed as a range) associated with certain outcomes will help to
manage risk (both upside and downside). Various verification procedures exist to
eliminate resource risk during the entire resource and reserve definition process.
Simonsen and Perry (1999) provide a summary of these typical tools, which are
presented in Table 11.
Table 11: Typical MRM activities with the corresponding technique and associated data type.
Drill hole logs
Scan lines
Geotechnical Data
Diamond Drilling
Core logs
RC Drilling
Sections and plans
Channel chip sampling
Existing mapping and
Sample preparation
photographic records
Various technique available Assay certificates
depending on commodity
Density report
Diamond core drilling
RC drilling
Rock mass classification
Rock density
RQD values
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Metallurgical Data
Ore testing
Recovery index
Milling behaviour
Data storage, retrieval and Metal grades
Data base
Rock mass classifications
Survey data
Lithological data
Interpretation of data
Mineral controls on orebody
Metal continuity - zonation
Geological model
and trends
Electronic mineralisation
model, maps and sections
Geological units
Frequency curves
Block model construction
3D co-ordinates
lithological units and rock
grade interpolation
Resource classification
Kriging variance
Sampling distance
Drilling density
In each of these activities there is clear evidence for specific risk-quantification
techniques within resource estimation. This process and overriding technical
responsibility for the outcome rests with the MRM department.
The extent of resource risk inherent in alluvial diamond deposits is, in fact, often
considered to be so great that certain funding institutions will not finance such
initiatives at all (Jurd, pers comm). The key financing downfalls within the alluvial
diamond sector include the fact that a proven reserve statement cannot by submitted
(refer to Section 4.1), as the confidence levels in preparing the mineral resource are
mainly inferred, which also implies that a bankable feasibility document cannot be
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prepared (Coetzee, 2004). Grade is typically a function of carats and continuity, two
parameters that are difficult to predict with high confidence. Mining activities are
typically nothing more than bulk sampling exercises, where discrete trenches are often
excavated individually (Coetzee, 2004). As there is generally limited technical and
financial ability to recover from negative planning, fluctuations and unplanned cash
flows, the alluvial diamond sector is precariously balanced. The 1. 5 ha mining permit
(MPRDA, 2002) is too small an entity for potential operators to produce sufficient
supporting evidence for funding opportunities, while the requirements of a mining
licence (preparation of a mine works programme (inclusive of a resource and reserve
statement) and social plan) are often far too onerous on the concession owners as a
result of the migratory nature of many of the activities and the low levels of financial
capacity. The alluvial mining sector requires some careful attention by stakeholders,
for ensuring the livelihoods of many communities in the Northern Cape and North
West Province are not adversely affected.
The challenge, therefore, is for junior and small-scale mining sectors to combine
applicable methods or tools of risk analysis and management to potentially lower
levels of resource risk. However, it must be realised that the inherent nature of a
deposit (high nugget effect for diamonds) cannot be altered.
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Risk quantification/analysis techniques
Menell, in his APCOM address in Cape Town in 2003, observed that “tools without
purpose are toys”, while Rozman and West (2001, p 501) state that “no single tool
exists, which combines the many and varied uncertainties in a mining operation” (or
project). This evidence is support for the fact that risk analysis and quantification are
exceptionally difficult within a mining framework. Various methodologies have been
applied over time and continue to evolve as understanding of the overriding
uncertainties increases. By way of introduction to this section of the treatise, various
quantitative resource risk assessments that exist are (Mullins et al., 2003):
Sensitivity analysis of key variables, which provides good information on the
sensitivity of an outcome (e.g. NPV) to changes in the input parameters;
Reporting confidence levels for resource classes, this is rarely used, however,
in public reporting forums. (See section on SAMREC); and
Reporting the range of possible outcomes for variables such as tonnage and
In addition, other risk assessment techniques applicable to resource risk assessments
include (Smith, 1995):
Most likely case (base case);
Best case/worst case;
Decision tree;
Monte Carlo simulation; and
Root sum of squares procedure.
The objective of this section is to introduce some of the more widely applied risk
assessment techniques in the MRM arena. Each will be outlined and relevant
examples of application will be explained, where appropriate. The overall size of the
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operation and/or deposit need not be a reason not to adopt certain of these
methodologies. In fact because of the greater element of risk in smaller mines the
need to begin applying such techniques is critical to ensure success. Risk analysis
quantifies exposure and losses to prescribed circumstances so that probabilities of
future losses or opportunities can be projected (Terblanche, 2002). In addition, one
should not lose sight of the overriding business objectives, which makes the most
important aim of risk analysis predicting the likelihood of a planned profit to be
achieved over a given period of time (Simonsen and Perry, 1999). Essentially, this
process provides answers to the following fundamental queries:
What can happen?
How likely is it that it can happen?
What are the consequences if it does happen?
Risk classification
The first technique or approach of risk assessment is called risk classification. A basic
approach has been to categorise risk as either known, known unknown or unknown
unknown (Toll, 1994). Risks can be categorised in tabular format, according to these
headings, where known risks are those circumstances where variability is common
and understood (resource risk). Known unknown applies to risks that have a low
probability (but are foreseeable) and will have severe consequences if they occur.
Unknown unknowns are very rare and therefore cannot be predicted. Typical
examples relevant to the junior and small-scale sectors are given in the table below.
Table 12: Example of MRM risks relevant to the junior and small-scale mining sectors
Risk classification
Known unknown
Generally poorly defined mineralisation models,
hence impact on overall recovered grade.
Risk exposure due to sudden loss of key MRM
Events of natural disaster that could destroy the
Unknown unknown
entire deposit e.g. landslides (clay deposits), 50year floods (alluvial gold and diamond deposits).
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Another widely used application for classifying risk is according to a
probability/impact risk matrix where risk is defined as the product of probability of
event (frequency) and magnitude of loss/gain (severity). By combining probability
and impact scales an overall risk rating can be assigned. To be able to accurately rank
the above risks the two variables (probability and impact of the risk occurring) need to
be used in conjunction with each other. Risks with high probabilities and high overall
impacts will need attention and aggressive risk management strategies. Various
authors have illustrated an application of this (Pitzer, 1989; Terblanche 2002). The
two variables considered in the application of this methodology are:
Frequency of loss = actual number of times the same, or similar, loss occurs;
Severity of loss = size or cost of the loss to the organisation or mine.
It is the relationship between these two variables that is then represented in the form
of a matrix calibrated to specific circumstances. A risk exposure that has both a high
frequency and a high severity of occurrence should be given the greatest consideration
for elimination or control. The total amount (or value) of risk is a product of the
probability of the risk occurring (a percentage) and the overall cost, if the risk were to
Total risk = Probability * Amount
Examples of possible probability and impact scales are as follows:
Probability Scale
No probability of risk becoming a reality
Certain probability of risk occurring
Impact Scale
Essentially, this answers the question “What would the impact on the original
objective be if the risk were to occur? The use of ranked values (very low –
low – moderate – high – very high) as the answer provides the impact scale.
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The effect of the impact would be felt in three ways by the company and/or
operation. The impact could affect either the overall project cost, or time
(duration to completion), or quality (sometimes a delay may be avoided but
quality may be sacrificed; for example, quicker drilling rates but poorer core
recover and quality).
From this process essentially four main categories of risk exist. These are:
High probability - high impact;
Low probability - high impact;
High probability - low impact; and
Low probability - low impact.
A practical application of the risk matrix process was undertaken in the selection of a
suitable or appropriate small-scale mining method for a travertine deposit in the
Eastern Cape (McGill, 2003). Travertine comprises deposits of fresh water limestone
formed by precipitation of calcium carbonate from hot or cold mineral springs. It is
very soft and often quite porous. The two critical criteria assessed in the evaluation of
potential mining methods were the overall cost and the applicabiliy to small-scale
mining. The mining methods were ranked accordingly (Table 13). The criteria for
each method were rated from 1 to 5, i.e. low to high ranking.
An alternative method to the probability/impact matrix described in the literature is
the use of a project success matrix (Oosthuizen et al., 1998). A weighting to various
success factors is given for a specific project and then these are individually scored.
Essentially, this is the inverse to a probability matrix but this approach has the ability
to pinpoint areas not meeting certain success criteria and that, therefore, could be
potential obstacles to the success of a project.
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Table 13: Matrix for determination of a mining method for a potential travertine deposit
(McGill, 2003)
Chain saw
Stitch drilling
Wire saw
Suitable for travertine mining, but high
capital cost.
Not suitable for SSM due to size and
capital costs.
Suitable for SSM, but need suppliers
and affordable expanding clay/cement.
Suitable for SSM but expensive if
diamond tipped equipment is used.
Suitable for travertine mining since the
High pressure water
quarry is next to the river, but method
needs to prove its applicability and
reliability. Environmental constraints.
In summary, various methods of risk classification exist. Those described in this
section include the categorisation of risk, the use of a probability/impact matrix, as
well the application of a project success matrix. Each of these methods can be applied
adequately to the junior and small-scale sectors, as each of the matrices is designed
specifically for the particular operation. It would prove beneficial to many smaller
mines to apply these easy techniques. To further illustrate the use of a
probability/impact matrix a case study is provided in Appendix A.
Hazard and operability studies (HAZOP studies)
HAZOP studies are techniques adopted from the safety and health aspects of
processing plant design and chemical-related sectors. These techniques have been
extended into the mining sector with much success. It was discovered that traditional
approaches to plant design often missed critical weak points. HAZOP studies were
developed during the 1960s to systematically identify potential hazards and operation
problems in new designs (RSC, 2001). The results of the HAZOP process are
recommendations for design changes.
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Fault-tree/decision tree analysis
Fault-tree analysis typically considers a key effect together with a certain number of
underlying causes. This key effect is the “top fault”, with certain interrelated and
underlying causes making up the branches of the “cause tree”. Fault-trees enable the
probability of a hazard to be determined while the probable consequences of the
threat, the cause tree, are identified. The causes in a fault-tree may be considered to be
either dependent or independent of each other. Decision trees contain decision points,
usually represented graphically, where the decision maker must select from several
available alternatives (Kerzner, 2001). Chance points are then included, which
represent the probability of an expected outcome occurring. The application of faulttree analysis is a valuable method to compare alternatives.
Fault-tree analysis has been used by Cockram et al., (2004) to examine the impact of
specifications and procedures relating in particular to remnant mining scenarios. The
study revealed that mining without consideration for procedures exceeded the study
threshold, while the appropriate specifications satisfied the applicable criteria.
Ultimately the mine (Harmony Number 2 shaft, Orkney) was able to determine using
fault-tree analysis whether mining remnants according to the specified procedures was
economically viable or not.
An example of the application of fault-tree analysis to the small-scale mining sector
considers the following problem. In small-scale gold recovery the current technique
most commonly applied to concentrate gold is through the use of a sluice box and a
Chinese blanket. The feed material is passed over the blanket in the sluice box
trapping the heavier gold particles in the dense weave of the material. All other
material reports to the tailings (usually into a river or pool of standing water). An
alternative approach to the sluice box is a stepping pump concentrator, recently
developed by the CSIR and tested in South Africa, Ghana and Mali. The mechanical
device is a density separator, where feed material is passed into a conical basin that is
agitated with water through a nozzle, resulting in a basic cyclone effect. All the
oversize is removed manually, leaving the heavier concentrate in the bottom of the
bowl. The hypothetical problem concerns the choice of implementing one of these
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two methodologies on an alluvial gold recovery site (Figure 11). The associated
probabilities of success are given in the form of a decision tree in Figure 10.
Various washing cycles
using secondary and tertiary
material. Potential = 20%
Probability =
0.4 x 0.2 =0.18
Sluice box and Chinese
blanket. Potential = 40%
Choice of technology for
Small-scale gold recovery
Primary concentrate as feed
for the stepping pump
Potential = 80%
Probability =
0.4 x 0.8 =0.32
Various concentration cycles
Potential = 70%
Probability =
0.6 x 0.7 =0.42
Straight feed and single
stage concentration
Potential = 30%
Probability =
0.6 x 0.3 =0.18
Stepping Pump Concentrator
Potential = 60%
Figure 10: Example of an application of a decision tree (figures are illustrative)
This example illustrates that by graphically depicting the various choices available
and allocating numerical values (numbers used for the purpose of example only) for
associated potential the associated probabilities for each method are expressed. From
the above example the method with the greatest potential considers various
concentration cycles of the stepping pump, while the lowest potential is the use of the
sluice box and Chinese blanket for the entire process.
University of Pretoria etd – McGill, J E (2005)
Sluice box
Stepping pump
Figure 11: Comparison of the stepping pump concentrator (foreground) and sluice boxes
(background) for small-scale gold recovery.
Sensitivity analysis
A sensitivity analysis comprises the changing of a value of (a) key parameter(s)
within a specified range from the initially estimated value. Factors usually considered
are those that have the greatest influence over the value of the project. Possible
variables include tonnage, grade, metal price, metal recovery, capex and opex costs.
However, usually no attempt is made to estimate the probability that the parameters
will take these values (Rendu, 1999). Sensitivity scenarios could be opex, capex,
commodity pricing or even project delays (plus or minus 10% and 20%). Sensitivities
may be simplistic, as changes may have a knock-on effect into other areas. This
conservative method will, however, provide a best/worst case result.
Other useful parameters include how much the NPV or IRR will change in response
to a given change in input variable, other things being constant (Hartley et al., 2000).
One begins with the “base case” (which is a set of economic conditions and operating
plans felt to be the most probable case - for example, calculation of the expected
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NPV), and then, in turn, adjusts the input variables by a fixed percentage and then
recalculates the NPV. These changes are then graphed. An example of this resultant
graph is provided in Figure 12.
R 45,000,000
R 40,000,000
R 35,000,000
NPV (Rand)
R 30,000,000
R 25,000,000
R 20,000,000
R 15,000,000
R 10,000,000
R 5,000,000
% change in variable
% revenue variation
% capital variation
% operating cost variation
Figure 12: Example of a sensitivity analysis undertaken on a potential junior-scale operation in
The sensitivity analysis (Figure 12) was completed using the variables revenue, capex
and opex. From the figure it can be assessed that variations in total revenue will have
the greatest impact on the NPV of the project, due to the slope of the line. The inputs
to the revenue calculation were tonnage, grade, mine call factor, recovery, and gold
price. All these factors are affected by the production rate. The determination of a
viable production rate is critical for preparing a DCF model, which will be used as the
basis for a sensitivity analysis. Various tools are provided by O’hara (1980) to
estimate operating costs. In this scenario, operating costs have the least impact on the
NPV, when compared to opex and capex.
The impact of each of these parameters is even more noticeable on junior and smallscale mines. The usefulness of sensitivity analysis is in providing information to the
emerging operator with regards quantifying and prioritising risks and where best to
mitigate them. Institutions evaluating deposits for small-scale operation should share
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the outcome of this technique (if prepared during the evaluation process) with the
successful recipients of funds.
Subjective or “expert” judgement
A typical expert judgement technique is the Delphi method, named after the Greek
oracle. It is a group-decision process about the likelihood that certain events will
occur. They represent the opinion of the group rather than a statistically significant
sample set (Gordon, 1994). An anonymous panel, chosen as a group of experts, makes
predictions on potential risk factors and outcomes to a scenario, and then the results
are collectively pooled. This method is particularly useful, as the experts are not
required to be in the same place. New predictions are then made based on this
individual feedback. Various reiterations of the process are possible; however, they
add to the duration of the entire process. Gordon (1994, p 10) states that “no better
way exists to collect and synthesise opinions than (the) Delphi (method)”.
This technique would potentially be very useful on a strategic level for analysing the
diverse opinions of the various role-players and stakeholders within the junior and
small-scale mining sectors. These sectors have been the focal point of numerous
conferences and workshops but remain fraught with challenges. This subjective
judgment technique could be applied to establish strategic outcomes of and
resolutions to the numerous challenges within the sector.
Classic statistical techniques
Classical statistical techniques form the platform for a variety of techniques and tools
applied to understanding mineral resources and reserves. The discipline of
geostatistics deals with statistical tools and measures applied to the geological and
mining environments. The aim of these techniques is essentially to describe existing
sample data as well as to infer and predict potential grade values at locations not
sampled (Clark and Harper, 2000).
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Such techniques are particularly relevant to junior and small-scale operations where
any sampling and/or grade data can easily be assimilated statistically. The best
starting point is to take known data and understand it by producing descriptive
statistics. The measures include the mode, median, mean, range, variance, skewness,
kurtosis and coefficient of variation (Clarke and Harper, 2000). Once the
characteristics of the actual data are known it is possible to begin inferring or
predicting potential grade values for unsampled areas or localities. It is this data that is
used in procedures such as kriging and for constructing semi-variograms.
Certain geostatistical applications can be undertaken by individual operations but the
potential also exists to outsource such competencies to qualified specialists. This
would be particularly necessary for the delineation of resource and reserves to comply
with SAMREC requirements (refer to Section 4.1). The advantage of having a good
statistical knowledge of the orebody will go a long way to reducing a variety of risk
types. The underlying importance of sound geostatistical data is to be able to
accurately predict where suitable revenues can be achieved to ensure the long-term
sustainable development of the mine.
Monte Carlo simulation
Monte Carlo simulation utilises random values or percentage variations of various
assumptions, which are then used to provide a probability description of a project’s
viability (Rozman and West, 2001). In this way the Monte Carlo simulation process
attempts to create a series of probability distributions for potential risk items,
randomly sample these distributions, and then transform these numbers into useful
information that reflects a real-world situation (Kerzner, 2001).
Heuberger (2005, p 76) explains that “the term ‘Monte Carlo’ originated at Los
Alamos during the Manhattan project when scientists used a roulette wheel to
generate random numbers”. For Monte Carlo simulation to be truly representative,
certain conditions need to be in place. These are (Heuberger, 2005):
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The model must be an accurate representation of the operation under
The estimate must be realistic and based on actual exposure to the relevant
sector; and
The objective of the analysis must be clearly defined.
Owing to the high level of technical input required in this technique it would probably
not be widely applied on junior and small-scale operations. However, the value of
such a technique could reside with suitable technical consultants who could apply the
technique independently on a variety of mining licence and/or permit holders’ sites
within a single mineralised area, e.g. gold mining areas of the Barberton district,
Mpumalanga. The results of such a holistic Monte Carlo simulation, based on a
variety of data from available mines, could then be assimilated and distributed in a
way that individual operations could benefit accordingly.
Conditional simulation (range analysis)
Simulation techniques attempt to address potential shortcomings of other estimation
techniques by providing a range of realistic potential values within models (Thomas et
al., 1998). Conditional simulation is a tool for assessing the risk of predicted tons and
grade of any resource model. Conditional (sequential) simulation, therefore, produces
different possibilities of how the deposit might look in terms of geology and grade.
Essentially, numerical modelling at all levels of uncertainty occurs.
This method comprises 3D-simulated models of reality. Information/data used in the
process includes geological interpretation, data integrity, grade ranges, and
variograms (Glacken, 2002). In well-understood areas simulation models will be
similar (low risk) while in areas of reduced information the simulations will be very
different. These are, therefore, high-risk areas. However, through the process of
conditional simulation worst, best and in-between cases can be predicted. Usually
between 25 and 100 similar models are generated during the process of conditional
simulation (Figure 13). This technique is obviously better than other techniques that
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produce a single estimate. The simulation’s results can be analysed to quantify the
uncertainty associated with the overall resource (Dohm, 2003).
recoverable grade (%)
Risk in grade at 0.4% Cut-off
cut-off (%)
Figure 13: Graphical representation of the result of a conditional simulation process, for 25
series. The range of possible grades is clearly shown (Carey, 2002)
Conditional simulation allows the mine planning staff to assess the effects of shortterm variability in the deposit, including variables such as coal-seam thickness and to
quantify the risks associated with such issues as ore/waste classification, mine design
parameters, stockpile designs etc. It is obviously important to consider the integrity of
the simulation exercise where the number of simulations is observed and the
reproducibility of the variogram model and histogram are reviewed and verified. An
example of verification would be to generate variograms for the simulated data. This
should represent the same as the input variogram used in the initial phases of
conditional simulation.
Various forms of simulation methods exist and the most widely applied are sequential
simulation methods. These are either sequential Gaussian (which uses ordinary
kriging) or sequential indicator (which uses indicator kriging) (Glacken, 2002). It is
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important to choose a technique that suits the style of mineralisation and its associated
continuity. As all deposits are different, one technique should not be used in all
circumstances. Various examples as to applications of conditional simulation are
provided in the next paragraph. In summary, conditional simulation provides a tool
for detailed risk analysis, risk conscious mine planning, as well as decision making.
Table 14: Steps involved in the conditional simulation process (Snowden, 2002)
Diagnose risk requirements and define the risk profile
Understand the geological controls on mineralisation
Define the relevant mining and metallurgical issues affecting simulation outcomes
Validate the database and develop a geological model
Investigate the statistical behaviour of the mineralisation
Investigate the spatial continuity of the mineralisation
Determine the appropriate block size and point simulation grid dimensions
Choose the appropriate simulation method and parameters
Validate the simulation models against the input data and the continuity model
Composite point simulations to block simulations
Post process the simulations to address the risk outcomes
Produce a risk-qualified or optimised outcome
The following paragraphs provide certain industry applications for conditional
simulation. BHP Billiton adopts a process of conditional simulation to provide
quantified information on upside or downside potential (Mullins et al., 2003). There
are a number of conditional simulation techniques and the choice of technique
depends largely on the style of the mineralisation and its continuity, as well as on the
inherent statistical behaviour. One method typically applied by BHP Billiton is the
sequential Gaussian simulation. Here, the algorithm defines a random path through a
grid of nodes. Kriging of the nodes in the path generates a local distribution. A new
value is then given from this local distribution. This grade and associated position is
added to the nodes in the random path and the next node is simulated (and so on). The
generation of up to 200 simulations provides a distribution of grade estimates for each
block. It is these distributions that are use to calculate various probabilities of
occurrence. BHP Billiton has demonstrated this approach to quantify global or reserve
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risk, pit optimisation risk, phase pit risk, and mine scheduling risk (Mullins et al.,
Dimitrakopoulos and Fonseca (2003) demonstrate how conditional simulation was
used successfully to predict the variability of recoverable copper (including
metallurgical factors) and the associated risk within a Brazilian complex multielement copper deposit.
Another workable application has been provided by Sullivan (2003) in whose study
conditional simulation was applied to determine the underlying value of additional
drilling at a mainly copper deposit in northern Chile. Initially, the project was set at a
10% discount rate based on a certain level of drilling. Simulation exercises revealed
that the risk premium for not completing proposed additional drilling was 3.6%,
which meant the discount rate was raised to 13.6%. In other words, if the additional
drilling were not to be completed the project should be discounted at 13.6% which the
author stated equated to a reduction in the project NPV of USD 150 million (Figure
14). The additional funds spent on drilling would therefore be well spent. There is, of
course, a maximum amount of drilling too, reflected in the overall NPV distribution
curve below.
Figure 14: Impact of increased drilling on the distribution of project NPV (Sullivan, 2003)
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The potential applicability to the junior and small-scale mining sectors is similar to
the statement applied for the section describing the Monte Carlo simulation (Section
5.3.8.) where it is the opinion of the author that because of the high level of technical
input required (which equates to financial expenditure) this technique would probably
not be widely applied on individual junior and small-scale operations. Potential
application could be undertaken on a regional scale, however. There are definite
advantages to applying such techniques. The increased understanding of the orebody
will provide data to decrease associated MRM risk and, in turn, make funding
initiatives more likely.
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Tools for managing MRM risk
The aim of this section is to describe techniques for managing risk that have particular
relevance to the mineral resource sector. In addition is it crucial to note the
applicability of such techniques to in the junior and small-scale mining sectors. Often,
techniques may not be considered appropriate because of the high overall cost of
implementation, but this should not deter operators from perceiving the inherent
relevance of the technique and how techniques could possibly be “tweaked” for use
by role-players in the sector. Other reasons for not applying such techniques include
the overall integrity of the data. Date generation, capture and storage on smaller
operations is often not considered as high a priority as it is by larger operations.
Through capacity building, the underlying importance of such data to be used in risk
management tools - which would ultimately translate to greater funding opportunities
will be realised.
It is important to realise that one’s attitude to risk will dictate the potential strategic
options available (Pearce and Robinson, 2000). In situations where risk is favoured,
the range of possible strategic choice expands and high-risk strategies are more
acceptable. In a risk-averse environment certain strategic choices are eliminated from
the decision-making process before it even begins. Outcomes from past strategies also
have a profound influence on risk-averse managers. This is particularly evident within
the high-risk mining sector. Owing to the higher risk within the mining operating
environment profile managers are more prone to considering broader and more
diverse risk related strategies.
Bayesian approach
The Bayesian method uses objective data and subjective judgement to provide
probable outcomes (Glacken, 2002). This method is especially applicable within an
exploration environment where data is generally sparse, and data from similar
prospects in the same area tends to be used as conditioning data. This approach was
applied in exploration drilling phase at Target Mine, Free State, where the
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conditioning data was a borehole (ERO1) that intersected a stacked reef scenario. A
matching distribution was then applied from the known Loraine Gold Mine’s reef
distribution model. This approach allowed for further targeted drilling, which reduced
the risk associated with exploring in the wrong place. The obvious shortcoming,
however, with this approach is that comparisons are only possible in identical
situations, which seldom occur. For this reason, the method should be applied with
caution, particularly in the junior and small-scale mining sectors, where very sitespecific issues exist.
The discount rate in DCF models
The discount rate is a fundamental means of reflecting risk in discounted cash flow
evaluations (Smith, 1995). It is therefore imperative to estimate realistic projectspecific discount rates. The discount rate applied should be appropriate for an
individual case but also take into account the industry expectations for such a project,
risk factors associated with mineral projects in general, and risks related to the
specific project. When a discount rate is applied to junior and small-scale mines, in
particular, the discount rate will be higher than that applied to bigger mines. The
discount rate consists of three distinct aspects, where project specific risk will equal
the sum of these three values (Smith, 2003):
Risk-free interest rate – the value of long-term risk-free or “real” interest
(bank) rate;
Mineral-project risk – representative of the numerous risks as outlined in this
research; and
Country-specific risk – as supplied by various agencies in the form of bank
ratings, where it is important to consider both a current assessment plus
historical data. (Refer to Section 5.2.4.)
It could be argued that a certain amount of country risk is also incorporated in the
risk-free interest portion. Each country’s inherent economic situation will be reflected
by the independent bank interest rates. In addition, a variety of additional factors is
used to establish country risk rates as provided by, for example, Standard and Poor’s.
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(Refer to Section 5.2.4.) A more representative project-specific risk value will
therefore comprise the sum of these three values, rather than just that of the first two.
However this point is not without debate (Holmes pers comm; Smith, pers comm;
Jurd pers comm).
From a survey generated by the MES in 1996, Smith was able to obtain data on
discount rates applied by industry to various stages of mining project life-cycles
(Table 15) and compare this with conceptual values. All 33 sample points were from
Canadian operations, which meant that any overriding country-risk elements were
neutralised (Smith, pers comm). (This study is currently being updated to include
cross-continental data.) It was shown that the discount rates applied on gold
projects/operations were 2 - 3% lower than those used for base metals. This
conclusion has been attributed to the capital asset pricing model used in the
valuations. This conclusion could further be explained by the fact that it is easier for
gold mines/prospects to obtain bank loans, as a result of the sophisticated hedging
methods and other financing tools available to the gold sector. This scenario is
particularly relevant to the junior sector where gold is traditionally viewed as “money
in the ground” therefore easier to fund and enabling the lowering of the applicable
risk rate as opposed to other commodities.
Table 15: Summary of discount rates (%) in concept and practice (Smith, 2003)
Level of Study
Conceptual study
“Real world” values
Smith (1995)
Order of Magnitude
MES Survey - 1996
Base Metal
11.6 – 23.1
11.1 – 24.2
6.9 – 15.7
10.1 – 16.5
4.8 – 12.8
8.5 -14.2
1.6 – 9.1
6 – 11.3
In the context of South African junior and small-scale operations ABSA Corporate
Bank currently applies a discount rate of 16% to all mining ventures considered by the
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resource division, independent of size (Jurd, pers comm). The reworking of dumps
and the processing of aggregate from borrow-pits is not deemed as mining per se and
such investments are accorded lower discount rates. Not all commodity groups are
supported by banks, like ABSA, for various reasons. For example; alluvial diamonds
are very difficult to evaluate as a reserve status, and cobalt suffers from potential
oversupply, as well as associated country risks (Jurd, pers comm).
Grade/tonnage curve
The most important tool within the MRM toolbox is the grade/tonnage curve or the
VAC, as applied by AngloGold Ashanti because it allows for the derivation of cut-off
grade and the average mining grade above a certain grade cut-off, as well as the
resultant tons available above the cut-off (Figure 15). Each deposit would have its
own unique curve because of the grade distribution in the deposit, but certain deposit
types display internal similarity.
Planning Resource component is 7.75% of m2
and 10.38% of contained gold in restated
Mineral Resource - March 2001
1012 1104 1196 1288
Cutoff cmg/t
1380 1472 1564
1656 1748 1840 1840
Total Square metres
Square metres minus planning resource
Total Progressive cmg/t above cutoff
Progressive cmg/t minus planning resource
Figure 15: A typical value-area curve (VAC)
Progressive cmg/t
above cutoff
Square metres
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The grade/tonnage relationship is also dependent on the block size used in the
calculation. Using too large a block size will underestimate the potential to mine
selectively, while using too small a block size will result in an optimistic view of the
degree of selectivity that can be achieved (Dewar, 2001). The grade tonnage or VAC
curve is the overall result of the geostatistical evaluation process and, therefore,
represents the overall quality of the orebody. Other important derivatives include the
estimation and comparison of grade/cost as well as grade/volume relationships. DCF
analysis and risk analysis techniques related to this will allow constant re-optimisation
of the orebody, according to fluctuating financial circumstances. Certain shortcomings
do exist with this technique. These shortcomings include the fact that the actual grade
distribution or the continuity of grade between ore blocks is not described.
As already stated, the generation of a grade tonnage curve is one of the critical
outcomes from geostatistical evaluation. This technique is more suited to deposits of
high-value commodities like gold, platinum, and iron-ore for example. The
methodology requires a good level of basic geostatistical data (refer to Section 5.3.7)
and would probably be the most beneficial to junior-scale operations. A geostatistical
consultant can ensure SAMREC compliance (Section 4.1) if this is required.
Geological modelling
Parameters fundamental to obtaining the knowledge required for geomodelling relate
to geochemistry, geophysics, sampling for grade, mineralogy and geological structure.
Such information forms the basis for meaningful geological modelling. Examples that
have been referred to by Viljoen (2000) include facies modelling, ore shoot
modelling, stratigraphic and structural modelling, and the use of geophysics. In
addition, the relevance of 3D rock mechanical models of stress patterns, based on
information available prior to mining, should not be underestimated. The 3D
computer modelling process produces various virtual models of the orebody
(sometimes using wireframes) as outputs, based on this data.
Irrespective of the modelling methodology applied, the final mineral resource is the
result of an estimation process. Interpretive errors will exist, as well as variability in
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the assay data and/or sampling results (Rozman and West, 2001). The correct order of
accuracy must, therefore, be assigned to the overall reserves and resources. It is
paramount that high levels of accuracy exist in the sampling design phase.
AngloGold Ashanti identified that risk is associated with the estimation of gold grades
and grade distribution due to inadequate knowledge (Dewar, 2001). Certain internal
AngloGold Ashanti processes existed on individual operations but these were highly
dependent on available data, techniques applied, knowledge of the controls on the
mineralisation, and the judgement of those making the estimations. The greatest risk
areas in a geological model are summarised as (Dewar, 2001):
The accurate delineation of limits or boundaries to the orebody, especially
where data is scarce or missing, to prevent an over- or under-estimation of
volume and tonnes;
The estimation of block grades from samples, which involves kriging, to
obtain a relationship between known and unknown data points;
Sampling and assaying errors through systematic biases during the process;
mineralisation models as a foundation to the geomodelling process.
Dohm (2003) states that an effective estimation process is dependent on both a
geological model based on a thorough understanding of the mineralisation, and an
appropriate estimation technique, such as kriging. Deraisme and Farrow (2003)
describe how, through geological modelling, a relationship between the number of
planned boreholes within a diamond kimberlitic environment and the confidence in
the estimates of annual production, roughly corresponding to a mining level, can be
Ashanti operations introduced various methodologies to geomodelling (McGill,
2000) certain commonalities in approach were proposed for the reduction of
associated risks. (Refer to Appendix B.) Within AngloGold Ashanti the geological
model was defined according to various developmental stages (McGill, 2001a).
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Initially, reef polygons were created in 3D space using Cadsmine software, revealing
fault cut-offs. A second stage involved the extrapolation of these surfaces, which gave
a holistic view of faults and intrusives. Finally, it was possible to combine various
geological parameters and grade data to provide a holistic tool for accurate geological
predictions beyond the existing mapping sheet. This holistic model was then used for
geostatistical evaluation.
Of concern is the misconception that a 3D geological model is merely a static graphic
or “pretty picture”. The true value-add of a geological modelling system lies in how
the information derived from the model can be incorporated into the holistic MRM
system. The benefits of such a modelling system are both soft and hard:
Soft Benefits:
Improved communication of information between various people or
departments on mines;
The distinction between luck and good management practices;
Potential to encourage participation at all levels in the operation; and
The interrogation of the model and its potential for improving communication
at all levels.
Hard Benefits:
Allows optimal mine design and scheduling;
Reduces the likelihood of accepting flawed interpretations;
Provides for accurate geological reconciliation year on year;
Plans generated will be defensible and will expedite drafting of accurate
drilling budgets and scheduling of the resource;
Increases the likelihood that the project will follow the plan, which reduces the
panels to be stopped and started in any given month; and
Highlights structurally complex (risky) areas from a distance.
Such models will also be of use to rock engineers, mining engineers and any other
interested party, as they facilitate proactive management of the mineral resource.
However, often a mental shift is required to adapt to the understanding of such 3D
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systems. Identification of key risk areas is the main area where geological modelling
can help reduce risks associated with mining. Computerised geological modelling is a
key advancement for effective MRM. The challenge is to ensure that the
geomodelling process is integrated into the existing MRM systems and ensures
maximum value-add to operations in this way.
The AngloGold Ashanti example provided in Appendix B is indicative of how
geological modelling is incorporated into the MRM system on larger operations. It is
prudent to question the effectiveness of such methodologies for smaller operations.
The acquisition of geological modelling software and the associated capital outlay in
terms of computer hardware and training of personnel is crucial, in the opinion of the
author, if the junior operations want to compete effectively and continue to operate in
an efficient manner. An example of the application of 3D geomodelling by a junior
mine encountered by the author involved the (then) Bosveld Gold Mine in Pongola.
Here, the mine had never considered computer modelling of the shear-hosted
mineralisation. When the Bosveld Mine management acquired the operation, one of
the first management decisions involved carefully updating all the mapping sheets,
which were ultimately captured in a computer geological model. The process was
time consuming and expensive, but the gains and ability to locate additional
development-drilling platforms to expose the richer reef types added two very much
needed years to the LOM. Owing to the nature of the deposits exploited by the junior
and small-scale sectors, the value addition through the application of geological
modelling is limited and can be considered unnecessary. 3D modelling expertise
could also be applied on a contract basis to update mine models and need not be used
on a continuous basis, as it is in larger operations.
3D seismics
3D seismics has been used as a technique of mineral resource risk reduction with
much success in a variety of geological environments. Extensive 3D seismic surveys
have been undertaken within the AngloGold Ashanti mining house as well as the
Target Mine of the gold sector. 3D seismic techniques have also been proven
successful on the platinum mines.
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3D seismics is a geophysical tool to provide the gross structure and depth of
prospective stratiform ore horizons (Figure 16). In addition, through careful analysis
of 3D seismic attributes, validated borehole control, and direct geological
observations, seismics can provide important information on small-scale faulting and
variations within the ore zone conglomerates. Stuart et al., (1999) commented that
modern 3D seismic evaluation techniques, applied prior to mine planning and
development, can provide detailed geological information that reduces risk and
increases mining efficiency and safety
The application of 3D seismics at Tshepong Mine, Free State, enabled structural
interpretation that was used to plan access to a 1 000 000m2 block of ground, as well
as to a decline system. In addition, geological confidences and associated mining risk
factors could be adjusted accordingly (McGill, 2001b). The potential economic
impact of geophysical mineral resource risk-reduction techniques was further
demonstrated at Impala Platinum, where 3D seismic surveys were undertaken by the
mine on the Western Bushveld during 1998 and 1999, covering 25km2 and 45km2
(Mellowship, 2000). The associated total project costs were ZAR 720 000/km2 for the
25km2 survey and ZAR 600 000/km2 for the 45km2 survey. When compared to a
conventional drilling programme, the survey costs equated to 2.4 boreholes per km2.
The capital costs for a major shaft system to access the same size block of ground
were estimated (1999) to be ZAR 1.6 billion. Therefore, the cost to undertake such a
survey is <1% of the capital investment.
Borehole radar as another 3D geophysical technique has successfully been applied on
mines to determine reef geometry before mining begins. Having this knowledge
before mining occurs allows for optimal ore extraction to occur and reduces the
related mineral-resource related risk considerably. Borehole radar has been
successfully applied on the Ventersdorp Contact Reef (VCR) at AngloGold Ashanti’s
Mponeng Mine to site-stabilising pillars in low-grade areas, as a replacement for the
traditional standard grid layouts (du Pisani and Vogt, 2004). The gold value locked in
one underground support pillar was estimated to be in the order of USD 2.6 million.
Positioning such support pillars in low-grade areas, as delineated by the borehole
radar analysis technique, allows significant economic potential to be unlocked.
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Figure 16: Representation of the basal reef horizon pick in a 3D cube – Tshepong Mine
3D seismic techniques, used either on the surface or by means of underground
borehole radar, can provide extremely useful geological data that goes a long way to
reducing mineral resource risk. However, accessibility to these techniques is restricted
to mining operations or companies that have significant capital expenditure budgets
and resources to implement or contract geophysical services. The applicability of such
techniques for the junior and small-scale sectors is questionable. However, in the
current dispensation and conversion of mining rights, certain operators may obtain the
marginal “discards” of larger established operations. The case might be that such
techniques were applied over such areas and the information and data-sets can be
acquired by the junior mines. Therefore 3D data, as a tool to reduce mineral resource
risk, should not be overlooked.
Mining due-diligence studies
Traditionally due-diligences were carried out on functional areas such as legal and
financial (Anderson and Tingley, 1988). Mining technical risk appraisal has the ability
University of Pretoria etd – McGill, J E (2005)
to assess all factors impacting on the operation and/or sale condition in a structured
way. To appraise the impact of future risk requires the application of business duediligence. Mining due-diligence studies constitute the backbone to most sound
investment decisions within the minerals sector. The completion of a due-diligence
study is generally a phased approach, which considers the following in order:
resource/reserve calculation and verification; identification of key technical risks;
assessment of production volumes and costs – based on a production plan and
utilising the given infrastructure and proven reserves; and market analysis and
financial analysis (Anderson and Tingley, 1988). During each phase, until the
completion of feasibility, gathering and analysing data on the orebody and markets
reduce the degree of various risks. It is apparent, therefore, that within the duediligence report various techniques are used to adequately analyse and evaluate all
aspects of the operation or project.
Mineral investment evaluation, of which technical due-diligence is key, is further
complicated through each mineral investment possibility having its own singular
combination of risks and opportunities (Tingley, 1990). This unique combination
considers all aspects, including that of the mine/operation, available infrastructure,
political environment, and environmental aspects etc. Even proven reserves (refer to
SAMREC, Section 4.1) can differ materially in both type and degree of risk.
Through timely involvement of an independent technical auditor, responsible for the
formation of a feasibility and/or independent technical audit, risks associated with
seeking outside finance can be addressed. Technical questions can expose issues that
can potentially delay or jeopardise raising finance (Cole-Baker and Bower, 1998). In a
best practice situation, due-diligence audits should be repeated at different stages of a
project’s development, as more information becomes available and conditions are
better understood (Rozman and West, 2001). In other words, risk assessment through
due-diligence should become an iterative process.
Mining due-diligence reports are critical tools for the assessment of prospects under
consideration for the junior and small-scale mining sectors. All funding institutions
require such documentation and often may duplicate or re-do the entire feasibility
process in-house for clarification. Without such documentation most ventures would
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not be undertaken. Unfortunately, the cost of acquiring such documentation is often in
itself prohibitive for the potential entrepreneur. Vehicles such as the NSC are in place
for technical service providers to the DME to complete such studies on behalf of
successful applicants.
Reconciliation plays a very important role in the evaluation process. It is one of the most
crucial tools for any evaluator and is used to check the confidence of the evaluation. It is
through reconciliation that the geology model, variograms, local area means used, and
other assumptions are put to the test (AngloGold Limited, 2001b). Through an effective
reconciliation process effective learning about the orebody occurs and this information is
integral to future forecasting for the deposit.
Reconciliation entails the comparison between ‘planned’ grade estimates (kriged
predictions) and the ‘actual’ estimates (kriged together with additional/new sampling
points) of kriged blocks (Figure 17) to kriged values for the same blocks once mining
and sampling have taken place. Through reconciliation, the evaluation process can be
refined and optimised so that the best possible estimation of values for the particular
orebody can be produced.
Reconciliation, therefore, serves as a value check. Factors such as geology and mining
changes (in the case where a mining plan is reconciled) need to be excluded from the
exercise. The planned mining and actual mining may differ and, therefore, differences in
the value estimates can be expected. The mining plan should then be reconciled so that
the errors associated with mining can be eliminated. For standard reconciliation the
effect of mining is removed by reconciling kriged grid blocks only.
University of Pretoria etd – McGill, J E (2005)
y = 0.9817x + 26.568
R = 0.8894
1000 1200 1400 1600 1800 2000 2200 2400 2600 2800 3000 3200
March vs December
Ideal regression slope
Linear (March vs December)
Figure 17: Regression plot as a comparison of kriged block estimates for December 1999 and
March 2000 on a mine. The original estimated values (December 1999) are compared to
re-estimated samples on the basis of stope sampling. As the scatter plot reveals a good
correlation (slope approaching 1) the estimation process is deemed accurate
(AngloGold Limited, 2001b)
The advantage of a properly conducted reconciliation exercise is that it allows the
MRM practitioner to accurately predict the grade coming out of a mine, which, in
turn, equates to a better prediction of expected revenues. Reconciliation is a crucial
tool in assessing the effectiveness of planning, which is essential in management. The
required data needs to be collected during the mining process. Such a requirement
necessitates effective planning, which is, unfortunately, often lacking in junior-scale
operations. The overriding desire to mine for “now” rather than consider the forward
plan is one of the greatest impediments to successful MRM implementation on junior
and small-scale operations.
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Risk control techniques
In the risk management cycle (refer to Section 5.1) the first two activities are
identification and quantification. Once these activities have been applied to the junior
or small-scale operation, an appropriate method of eliminating or controlling the
particular risk must be identified. Various options exist (Terblanche, 2002) and will
be the main focus of this section. The key options for dealing with or alleviating risk
are the following:
Risk avoidance: ignoring or not participating in the risky activity or action;
Risk prevention: reducing the frequency of losses;
Risk reduction: based on the assumption that it is impossible to entirely
eliminate the risk, so reduction techniques are imposed to reduce the severity
of the loss;
Segregation of exposures: a mixture of both risk prevention and reduction
techniques according to which risky activities are isolated from other company
Risk transfer: often applicable in a legal or financial environment, where
identified risks can be moved to outside parties who are contractually
obligated to deal with them.
Each of these options has advantages and disadvantages depending on what level of
risk mine management is prepared to be exposed to.
Risk transfer can be alternatively addressed in the marketing of commodities by longterm contracts, forward sales and other hedging tools. Risk sharing is well represented
in the aluminium industry as a method for sharing the risk associated with the troughs
related to the commodity life-cycle. As seen below there are no risk-sharing options
that include the mineral resource management aspect of the business. Most options
cover financial aspects only, but have been included in these sections as an
University of Pretoria etd – McGill, J E (2005)
illustration. The various finance-related risk-sharing options available include the
Commodity sales at a straight percentage of the selling price;
Sales swapped for other metal according to an exchange ratio;
The commodity is sold at fixed prices; and
The commodity is sold by long-term call and put options (hedging).
Within the junior and small-scale sectors various options that can be considered as
methods of risk-sharing include:
The introductions of shareholders in the company;
The formation of joint venture agreements with technical partners;
The outsourcing of certain technical competencies to consultants; and
The purchase of varying levels and types of personal and corporate insurance.
Implementing any of the risk-control techniques mentioned above, has the ability to
provide the following opportunities for mining companies (Alexander Forbes, 2003):
Improving unfavourable financial ratios;
Guaranteeing and smoothing cash flows;
Obtaining discounted services;
Insuring conventionally uninsurable risks;
Releasing capital tied up in other portfolios; and
Smoothing commodity price cycles.
MRM-specific risk management techniques are varied. The purpose of the case study
provided (Appendix D) is to reveal certain of the risk-control techniques that have
been tested on some larger operations. The development and application of geological
risk domains at Tshepong mine provided an excellent framework for mine planning.
Undoubtedly, the challenge for the junior and small-scale sectors is to adequately
address risk issues and design applicable risk-control techniques for a particular size
of operations in different commodity environments. Similar techniques could easily
University of Pretoria etd – McGill, J E (2005)
be adapted for the junior gold operations in Mpumalanga and Pongola. Most surface
deposits are not as structurally complex as some gold orogenies, but other criteria,
such as slope stability, could be substituted.
University of Pretoria etd – McGill, J E (2005)
Table 16: Summary table setting out the applicability of risk management techniques to the South African junior and small-scale mining sectors
Stage of Risk Management Cycle2
Risk Identification (Types of risk)
Risk Quantification/Analysis
Technique available3
Applicability to junior and small-scale mining4
Management risk
Financial risk
Country risk
Operational risk
Technical risk
Resource risk
Risk classification (matrices)
Hazop studies
Fault-tree/decision tree analysis
Sensitivity analysis
Expert judgement
Classical statistical techniques
Monte Carlo simulation
Conditional simulation
All these risk types will interact with each other and
have individual influences on the overall success of
operations or projects within the junior and smallscale mining sectors. Of greatest importance to the
particular sectors is the impact of technical and
resource risk. High levels of resource risk severely
affect the alluvial diamond sector.
Very applicable and easy to implement –
Owing to limited process complexity, most operations
may not obtain any value from applying this method.
A useful tool to substantially quantify risk and
probability in various scenarios – recommended.
Where the detail in a DCF allows the use –
Potential strategic method for obtaining input from
High level of application possible – recommended
Requires large quantities of data and computation
Requires large quantities of data and computation but
potential exists for junior operations.
Refer to section 5.1
All techniques described in Section 5
Is the technique available suitable for application in the South African Junior and small-scale mining sectors and what opportunities exist for implementation?
University of Pretoria etd – McGill, J E (2005)
Stage of Risk Management Cycle2
Technique available3
Applicability to junior and small-scale mining4
Bayasian approach
Discount rate in a DCF
Grade tonnage curve
Geological modelling
3D seismics
Mining due-diligence studies
Tools for managing MRM risk
Risk control techniques
Risk avoidance
Risk reduction
Risk prevention
Risk transfer/sharing
Technique loosely applied currently to infer potential
by operations adjacent to larger established
Evidence reveals that not much variation exists in
discount rate applied but the DCF remains a critical
tool for evaluation purposes – recommended.
Potential exists for the “larger” junior operators
within the gold, platinum and iron-ore sectors, for
Very useful method to graphically obtain an
understanding of various mineral resource aspects,
recommended especially for more structurally
complex deposits. Use of relevant consultants
Expensive technique but allows high levels of
confidence for geological understanding and mine
planning. Acquisitions of old-order rights from
majors could involve the purchase of such data.
Integral to the holistic understanding of the operation,
most commonly completed on behalf a operation by
technical consultants – recommended, especially if
funding is required
A good measure for the level of confidence in grade
estimates but requires high levels of data, role for a
relevant consultant, but remains a highly
recommended approach.
The application of a variety of these methods is
recommended. The application of the planning
domain example can provide useful quantified
University of Pretoria etd – McGill, J E (2005)
The junior and small-scale mining sectors in South Africa undoubtedly make a
significant contribution to the livelihoods of a large proportion of communities,
particularly rural communities. Junior and small-scale operations are the central node
to numerous other add-on opportunities and developments. It is in the interest of the
development of South Africa to continue supporting and nurturing this sector.
The practice of risk management has been applied to most areas of general business
operation e.g. production and human resource management. The application of risk
management to technical areas is far more complex. Because geology is not an exact
science, accurate grade predictions are more difficult to make. Uncertainty is inherent
in each stage of resource and reserve estimation. One of the areas commonly exposed
by errors is the impact of over- and under-estimation of commodity grades (Glacken,
2002). Low levels of sound geological and evaluation data on many junior and
smaller operations equate to very high levels of resource risk.
One of the aims of MRM is, therefore, the minimisation of overall resource risk.
Methods to quantify technical risk are varied, as is the level of potential application in
the junior and small-scale sectors (Table 16). For some aspects of risk it may be
acceptable to rank variables by relating the probability and the consequence of failure
and representing the relationship on a probability-impact matrix. The relationship
between cause and risk is also important. By the removal of obvious causes, the
likelihood of the risk occurring will be reduced. As Pitzer (1998, p 58) states,
“unknown causes of unknown risks usually constitute the unexpected”. For the
average junior and small-scale operator avoiding the ‘unexpected’ equates to being
aware of the mineral resource and reserve being exploited and through capacity
building, where required, being able to quantify the risk accordingly.
The level of risk acceptability is generally determined by a risk-benefit analysis
(Dowd, 1997). This approach compares the cost of a project or operation with the
value of benefits generated. The greatest benefit to junior operators will result in
lower levels of resource risk and, consequently, a greater ability to obtain funding.
Other approaches to risk management available to the junior and small-scale mining
University of Pretoria etd – McGill, J E (2005)
sectors include: decision tree analysis; assessing the impact of uncertainty on finances
via a discounted cash flow model; and sensitivity analysis. Certain methods described
in the treatise may be best undertaken by technical consultants on behalf of mine
management. These methods include 3D seismics, geological modelling and
conditional simulation.
Obviously, the greatest hurdle for many junior and small-scale operations is the cost
associated with obtaining these technical services. The NSC is an avenue that exists
for junior and small-scale operators to apply and request that technical feasibility and
mine works programmes are completed on their behalf by relevant science councils.
In effect, however, this service equates to a consultancy service where the technical
fee is paid by the government on behalf of the successful applicant. The result is that
limited capacity building and skills transfer in related areas and disciplines occurs.
The operators remain dependent on outside individuals for financing outcomes and
decisions relating to their own permitted or licensed areas. A recommendation is that
the science councils (CGS, CSIR Mining Technology, and Mintek) play a greater role
in the provision of capacity building, as well as in the research and development of
technical techniques on a platform to enhance this sector’s position. Two examples of
current capacity-building initiatives include: the MQA-funded ASSM training school
at Mintek that provides entry level skills training on commodity-specific areas
(Mutemeri, pers comm); and the development of a board simulation by CSIR Mining
Technology, which demonstrates in a practical manner the range of decision making
required throughout the mine value chain as well as the actual impact of these
decisions on the underlying orebody and cash flow. Technical research and
development solutions that have been developed by the science councils to reduce risk
in portions of the mine value chain include the stepping pump concentrator developed
at CSIR Mining Technology (described in Section 5.3.4) and the I-goli mercury-free
gold-refining technique at Mintek (Mutemeri, pers comm). In addition, universities
should be encouraged to promote the mining-related disciplines of geology,
geophysics, geostatistics, mining engineering and metallurgy, for example, as viable
career options.
Finally, there are many voices in the junior and small-scale mining sectors in South
Africa. Many independent interest groups, organisations and stakeholders are
University of Pretoria etd – McGill, J E (2005)
practitioners and advisors to this sector. Confusion still exists over clear definitions of
the concepts of artisanal, small-scale and junior mining; legislative constraints exist;
and limited technology and skills transfer occurs. Within the working environment
small-scale activities often develop in response to poverty situations, operations are
often migratory and overall skills level and understanding low, while junior
operations struggle to obtain leverage to bridge critical financing hurdles.
Certain critical challenges undoubtedly exist for the South African government,
related ministries, as well as the servicing organisations and science councils. With
the increased need for assistance, mostly financial and capacity building in nature, the
key will be to deliver these services so as to enhance and uplift the development of the
community. Junior and small-scale mining has the ability to reduce poverty and
augment technology transfer, but only through formal and focused channels. This
treatise creates a platform by describing the characteristics of the sector and dealing
with minerals resource management issues in particular. The overall aim was to
highlight techniques to reduce mineral resource-related risk such, which, in turn could
make these prospects or operations viable for financing and/or investment
opportunities. No process can create additional value in the ground but these
mechanisms can go a long way to quantifying the inherent risk that exists and,
hopefully, to allowing the entrepreneur access to the intrinsic opportunities of the
emerging mining sector in South Africa.
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University of Pretoria etd – McGill, J E (2005)
Appendix A: Application of matrix-based risk classification
To illustrate the application of the matrix risk-assessment technique a case study of a
“Long Inclined Borehole” (LIB) drilling programme is described. Such a drilling
exercise is often costly and time consuming. Therefore, a reliable classification of
risks will assist in achieving success. It must be noted that such drilling programmes
are not normally undertaken by smaller operators but the types of risks described in
this case study could be applied to most drilling and or trenching programmes. The
objective of this case study is to illustrate one potential application of the matrix
technique in the MRM environment.
This particular LIB drilling programme was planned on a mineshaft such as to provide
the following key deliverables:
Accurate elevations for reef intersections on various mineable levels; and
Sampling of reef intersections allowing for overall reef quality (grade)
Geological features of recovered drill-core assist to define geological model
boundaries. These are boundaries where the geological model is believed to be of
higher or lower grade as a result of geological constraints. A drilling programme has
very tight time and cost constraints. Time is of an essence, as information must be
obtained and assimilated as soon as possible to facilitate future decision making. On a
shorter time-scale the underground drilling platform is also required for production
purposes. Drilling must therefore be completed timeously. Below are the three main
different categories of risks that could affect the outcome of the LIB drilling
programme (Table 17). A risk is an uncertain event or condition that, if it occurs, will
have either a positive or negative impact on the project objective. Certain of these
risks would, however, not be applicable to smaller operations with smaller staff
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Table 17: Three main areas of risk to the LIB drilling programme
Potential external risks
Cost escalation of drilling programme as a result of currency exchange circumstances
Drill machine availability
Material-machine spares availability
Labour issues
Intersection of methane gas during drilling
Underground conditions e.g. temperature of working environment
Project-based sources of risk
Technical complexity of achieving reef intersections by wedging
Physical working environment
Risk potential within the geology section of the MRM department
Allocation of clear authority for the drilling programme
Impact of other routine issues resulting in a increased workload
Top-down corporate assistance or interference
Geological expertise associated with rock-type recognition due to virgin area drilling
No grade being intersected by the core
Continuity of expertise due to any personnel changes
Effective management of drilling contractors
Risk associated with the drilling contractors
Technical constraints of LM 75 (machine–type) drilling
Technical expertise of the drilling crew
Technical constraints of successfully achieving wedging
Proper core recovery of reef intersections
Contractor-company communication between management and shaft team
Communication with geology section
Time of completion
Quality of service provided
Supply of machine parts in event of break-downs or machine failure
Below is the probability/impact matrix that was designed to assess all the risks (from
Table 17 above) of the LIB drilling programme.
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Table 18: Probability/impact matrix used to assess risks of a LIB drilling programme
Impact versus Probability
Very low
Very high
The overall result is indicated graphically by the given colours; where blue is low risk,
green moderate risk, and red high risk (i.e. very high impact and probability of
occurrence). Each of the risks applicable to the drilling programme is again listed
below with the colour indicating the overall level of risk, as determined from using
the above probability/impact matrix. The issues perceived to be of the greatest risk
(red areas) will be addressed in more detail.
Table 19: The three main areas of risk to the LIB drilling programme and the corresponding
assessment result, where red is high risk, green is moderate risk and blue is low risk
Potential external risks
Cost escalation of drilling programme as a result of currency exchange circumstances
Drill machine availability
Material–machine spares availability
Labour issues
Intersection of methane gas during drilling
Underground conditions e.g. temperature of working environment
Project-based sources of risk
Technical complexity of achieving reef intersections by wedging
Physical working environment
Risk potential within the geology section of the MRM department
Allocation of clear top-down authority for the drilling programme
Impact of other routine issues such as to possibly increase geologist workload
Top-down corporate assistance and/or interference
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Geological expertise for rock-type recognition in virgin area drilling
No grade being intersected by the core
Continuity of expertise due to personnel changes
Effective management and compliance of drilling contractors
Risk potential of drilling contractors
Technical constraints of LM 75 (machine–type) drilling
Technical expertise of drilling crew
Technical constraints of successfully achieving wedging
Proper core recovery of reef intersections
Contractor company communication between management and shaft team
Communication with geology section
Time of completion
Quality of service provided
Supply of machine parts in event of break-downs or machine failure
From the probability/impact risk matrix (Table 18), applied as described, the range of
potential severity for the individual risks is evident (Table 19). Due to the large
amount of risks provided only the high (red) risks will be considered in more detail.
The green and blue risks are those deemed to have a low probability of occurring and
if the risk were to materialise then the impact would also be low. Green ranked risks
have to be carefully monitored as left untouched while a moderate risk has the
potential to become a larger one. Red risks are those which, if arose, would have the
greatest impact on the project outcome. Due to the highly technical nature of this
particular example, most of the responsibility for the high-risk areas lies with the
drilling contractor.
Table 20: Risks ranked as high
Potential external risks
Drill machine availability
Material–machine spares availability
University of Pretoria etd – McGill, J E (2005)
Intersection of methane gas during drilling
Risk potential within the geology section of the MRM department
No grade being intersected by the core
Risk potential of drilling contractors
Technical constraints of successfully achieving wedging
Proper core recovery of reef intersections
Time of completion
Supply of machine parts in event of break-downs or machine failure
The proposed response for alleviating these ‘red’ risks, in each category, is set out
1. The drill machine is a problem for management until it is delivered on site.
However, once onsite machine availability longer poses a risk. Risk associated to
machine availability needs to be totally accountable to the drilling contractor and
is penalised with standing time claims. A possible dangerous intersection of
methane gas is always a risk by the mere nature of the service. Drilling contractors
by law have to take the necessary precautions in the event of a methane
2. The risk associated with no grade being intersected is one that which is always
carried by any geology department. The reason for any diamond drilling
programme is to help eliminate risk for further developments underground.
3. The contractor is responsible for all the identified drilling related risks. If a risk
becomes an actual event then no core would be drilled. Non-payment or reduced
payment for services would result. It is in the best interest of professional
organisations to limit these risks by implementing their own internal risk
management programs.
To minimise the risks to be retained by drilling contractors, such contractors need to
fully inspect their own risk management strategies. Even though the contractor may
carry the cost of the risks the drill-core will not be produced. The objective of the
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programme is to provide a project with good quality drill-core. It is then in the best
interest of company’s to have close ties with the drilling contractor and ensure that
common goals are always achieved. The ultimate goal is to ensure that the contractorclient relationship works well.
University of Pretoria etd – McGill, J E (2005)
Appendix B: Geological modelling as a method of risk reduction
In 2001 the importance of realistic 3D geological modelling at AngloGold Ashanti, as
opposed to mere computerised reproduction of underground plans, was demonstrated
by McGill and Mokoatle (2001). Effective geological modelling was used to identify
and quantify geological risk on both the Tau Lekoa and Tshepong shafts of the then
AngloGold. Tshepong Mine is now owned by Harmony.
The development of a robust, accurate and efficiently maintained geological model is
the most important deliverable required from any geology department. A distinction
needs to be made between the computerised reproduction of underground geological
plans and the creation of a holistic 3D model that is able to be viewed from various
perspectives. In addition, the value-adding role of a dedicated “geomodeller” on an
operation needs to be highlighted.
This appendix focuses on the modelling of reef and structural surfaces. In addition it
looks at simple techniques that can be utilised to quantify inherent uncertainties that
reside within 3D reef interruption models. The 3D reef interruption model developed
at Tau Lekoa and Tshepong highlights existing synergies on the operations, and
stresses the applicability of the organisational structure currently in place to varied
geological settings.
Compiling a reef interruption model is just one step in the formation of a holistic
geological model, but probably the most important for optimal macro mine design and
optimal extraction of the orebody. A holistic model will include data points in relation
to the main economic horizon in 3D space. Such data includes fault and dyke planes,
depth in the footwall, facies, mineralisation, and key isopach information.
There are few projects in deep level mining that rely on 3D modelling techniques to
ensure the high-quality geological input required to accurately estimate resources and
reserves. Of those sites that have digital models, very few link these to confidence
matrices. Likewise, little work has been completed with regards to uncertainty
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analysis techniques required to display due-diligence and quantify overall confidence
in the model or parts of the model.
Uncertainties and shortcomings, where present within traditional models, can be
hidden by short-term profits and go unnoticed on a large scale. These shortcomings
can potentially affect mine development, development costs, life of mine cash flows,
and may result in delays in the build-up to full production. This will result in a project
delivering lower revenues than were originally anticipated.
On a stope (small) scale, these shortcomings can affect the panels that need to be
stopped and those that need to be mined in any given month. This uncertainty impacts
on planned and unplanned crew moves, face advances, face length, ventilation
circulation, planned volume, planned gold, and hence the profit margins (cash flow)
of the business.
Although these shortcomings will not cause significant damage to the business in the
short term, it is the cumulative effect of these over time and across a number of
business units that is of concern and will affect credibility of MRM and mine
management. Consistent unreliability can potentially impact on the long-term value of
any operation. It was mainly this uncertainty, coupled with designer unfriendliness
and the hidden risk inherent in traditional plans that led Tau Lekoa to formulate a
four-phased approach to the creation of a 3D geological model and to a method that
would identify and highlight structural uncertainties hidden in traditional reef
interruption models.
University of Pretoria etd – McGill, J E (2005)
Tau Lekoa’s 3D Reef Interruption Model
3D Dyke Surface
3D Fault Surface
3D Reef Plane
Figure 18: Illustration of the Tau Lekoa 3D model showing fault, dyke and reef surfaces
The production of a 3D reef interruption model at Tau Lekoa Mine (Figure 18) is a
four-phased process. At Tau Lekoa, the creation of the 3D reef interruption model was
governed by the factors set out under headings below.
Transparency – The model generated must provide clear and unambiguous
information for users to understand the risks and impacts associated with mining
various reef blocks, as well as mining through adjacent reef blocks separated by
structural or other geological features.
Auditability – The model and its associated risk must be auditable. The data used for
compiling and fine-tuning the model must be stored in standard files and levels within
the software. Any interested party must be able to reference any information used in
generating the model and be convinced that the risk to the business as determined by
the model has been adequately quantified.
Materiality – The model must contain all of the information that could be required to
make reasoned, informed, and professional decisions regarding mine design and
University of Pretoria etd – McGill, J E (2005)
mining. This will ensure that the mineral resource is optimally extracted given the
constraints identified by the model.
Competency – The geological model must be generated by a suitably qualified and
experienced person with extensive knowledge of geology, as well as the various
software packages required to generate the model. All assumptions must be validated
through teamwork with the production geologists in order to ensure that the margin of
error is reduced as far as possible.
Tshepong’s 3D Reef Interruption Model
Through development of a mineralisation model at Tshepong Mine, and the generation
of a dedicated “geomodelling” and “data management” position, it was possible to
develop a holistic 3D geological model. The 3D model at Tshepong Mine was initiated
through the detailed modelling of a structurally complex portion of the mine. Work was
subsequently expanded to include other portions of the shaft, ultimately to cover the
entire Tshepong lease. Through GMSI software it was possible to quantify the impact of
these changes on the business plans for planning purposes. This was aided by colour
coding the reef blocks according to infrastructure accessibility by level. Applicable
data sources incorporated in the modelling process included raise line pegs, surface
and underground borehole intersections, and seismic horizon picks.
The basis of the modelling process adopted at Tshepong Mine provided a framework
and testing ground for the company wide “geomodelling process” that identifies
specific audit points during the process (McGill, 2001a). This ensures that actual data
elements are utilised to generate the model.
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Figure 19: Basal reef structural changes due to geological modelling on Tshepong Mine. The top
diagram represents the structure model in June 2000, while the diagram below
represents the structure in June 2001. Dramatic changes in geological structure are
revealed by colour coding mining levels
Figure 20: Example of the modelled reef (blue) and fault surfaces (red) of Tshepong Mine, with
borehole information included
University of Pretoria etd – McGill, J E (2005)
Appendix C: Application of the Turnbull Process
The London Stock Exchange commissioned a working group to address technical risk
management, and the process it generated is referred to as the “Turnbull Process”. It is
this process that AngloGold Ashanti, among other companies, adopted to ensure
implementation of the Turnbull Process AngloGold Ashanti identified certain
“headline risk areas” as a corporate initiative in 2001 (see Table 21). One of the key
risk areas was given as the “company’s mineral resource base”. This outcome resulted
in a process to understand and eliminate these key mineral resource related risks
(Dewar, 2001).
The main headline risk areas for AngloGold (and for most players within the mining
industry) are as follows:
Table 21: Key headline risk concerns as identified by AngloGold Ashanti in 2001
Commodity price
Currency – exchange rate
Interest rate
Counter party
Capital efficiency
Shareholder/stakeholder relationship
Employee relationships and performance
HIV/Aids levels
Legal and regulatory framework
Mineral resource Base
Political environment
University of Pretoria etd – McGill, J E (2005)
Stemming from this process and through risk analysis and assessment the following
factors were tabled as having the greatest impact on AngloGold’s South African
Table 22: Factors with greatest risk for AngloGold’s South African operations in 2001
Grade Estimation
Risk factors
Staff Levels/Skills
Note: 1 has the lowest significance and 9 will threaten the survival of the Group.
A probability of 1 will never happen and a 9 will definitely occur within the financial
period. Geological structure refers to continuity, accessibility, and dimensions of
It is therefore the goal of every mine to independently ensure that the above risk
factors are limited by way of transparent mineral resource management techniques.
Each mine’s business plan needs to be evaluated in terms of varying confidences.
These levels of confidence are categorised below.
Level l:
Assured plan – part of the business plan based on reserves and
approved capex
Level 2:
Reasonably assured plan – areas where resources may be converted
into reserves, as well as unapproved scoping exercises, which have a
reasonable chance of being approved in the current economic scenario.
Level 3:
Blue sky – the least confidant part of any business plan but contains
projects with upside price potential
Individual mines and operations have then developed certain methodologies to assess
the impact of mineral resource-related risk.
University of Pretoria etd – McGill, J E (2005)
Appendix D: Application of a risk control technique
Fault population or fractal analysis has been utilised at Tshepong Mine in order to
delineate areas of contrasting faulting intensity and, therefore, structural complexity.
A high degree of structural complexity often results in highly risky mining conditions.
Owing to the geological complexity of the mine a detailed geological analysis was
completed to quantify the actual amount of faulting and fracturing that would impact
production adversely. This information was used to sub-divide the mine into nine
“planning domains” – areas where the actual geological complexity is applied to the
production rate required. For each domain a faulting probability factor was calculated
as a product of macro and micro structural discounts. Each of these domains can be
plotted graphically, relating the amount of small-scale faulting to large-scale faulting
(Figure 21).
Small-scale Faulting > Increasing Risk
High Risk:
On-going contingency mine design likely
Lower than expected stoping efficiencies
Increasing Planning Risk
Low Risk:
Certainty of appropriate mine design
Accommodates high mining efficiencies
Large-scale Faulting > Increasing Risk
Domain 1
Domain 2
Domain 3
Domain 4
Domain 5
Domain 6
Domain 7
Figure 21: Planning domain risk profiles for Tshepong Mine
Domain 8
Domain 9
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Through this method, the overall geological risk per planning domain is quantified
and the potential risk is reduced by knowing which areas to avoid, or which require
more detailed geological information. Geological planning domains have been utilised
to profile the probability of geological structure hindering development and stoping
operations in different areas, and the potential impact of these on the business outputs.
The percentage of gold contribution from each planning domain is plotted on the xaxis (Figure 22) and used to quantify the potential impact on the business plan. The
result is a risk matrix chart that ranks the various domains as low, moderate or high
geological risk for specific planning time-frames. The knowledge of high-risk zones
coupled with the areas of potential high grade as indicated by the mineralisation
model in place on Tshepong Mine, allows for a targeted approach to the modelling
work required and reduces the risk for the overall mine plan. A domain with high
levels of uncertainty would be flagged as low risk if only a small gold contribution is
planned for.
Tshepong Mine
Geological Planning Domain Risk Profile
Potential Impact on the Business
Increasing probability
Intensity of Geological Structure
Increasing impact
Percentage Gold Contribution 3 Yr. Plan
Budget 2002-2004
5 Year Scenario Plan 4/2001
Figure 22: Risk reduction through implementation of a geological domain/risk
profile, Tshepong Mine
In the mine planning process, dependency on areas that are considered high risk can
be reduced until such time as more geological information is obtained. This approach
University of Pretoria etd – McGill, J E (2005)
is also useful when capital funding for new projects is being applied for. If the
planning domain of a new area is shown to be lower risk than areas within the current
Life of Mine plan then the MRM department is seen as actively striving to minimise
the overall geological risk profile of the operation.
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