Search Documents

By P Guj, J A. Bell

The valuation of early-stage exploration projects requires a valuer to take into account a large number of uncertain value drivers, the interplay among which may be non-linear. This paper examines some of the key value drivers including geology, target metrics, project area and maturity, the market and the psychology behind the decision-making process. The commonly accepted valuation methods and their underlying logic are outlined, including a view on why they evolved, what value drivers they attempt to address and their potential shortcomings. These methods include the multiple of exploration expenditure, geoscience rating, expected values and market based methods. The potential future valuation methods of replacement values and neural networks are also introduced along with how to minimise heuristic bias and error within the market-based approach.CITATION:Bell, J A and Guj, P, 2012. Exploration value drivers and methodologies, in Proceedings Project Evaluation 2012 , pp 17-28 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

By L Lorenzen, H Muller

"Every year a large number of projects are evaluated by small listed and unlisted mining companies that are hoping to find the ideal project, which will catapult them from a mining junior status to that of a mid-tier mining company. Usually this includes finding the æidealÆ or ærightÆ orebody and then developing a process which will allow cost-effective recovery of the valuable metals and the production of a saleable product. These dreams are seldom realised and there are a number of good and obvious reasons for this. Issues that are generally high up on the agenda for the smaller companies are: cost of developing a project before the feasibility study stage finding a suitable, or optimum processing technology financing of the project dealing with risk.The most expensive part of the development process for the small miner is often the exploration side of the business and finding the æidealÆ orebody. However, finding the right orebody will not be discussed in this paper. The æidealÆ orebody does not necessarily solve the problems of the mining junior, as much of the uncertainty lies in the process required to recover and produce the final metal product. Once a mineralised deposit has been identified and the grade at least reasonably qualified, the development of a suitable process becomes the driver to convert the deposit into an orebody. This paper proposes that a small exploration company has a very limited opportunity to succeed if it does not do sufficient homework before it identifies the æidealÆ orebody. The risk profile for the small mining company, by its very nature, has to be different to that of a major company and as a result the opportunities often lie in managing different and often new process options, which may be the key to bring such projects on line successfully.CITATION:Muller, H and Lorenzen, L, 2012. Project selection and process development for mining juniors, in Proceedings Project Evaluation 2012, pp 149-158 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

May 24, 2012

By B Maybee, L Fava, D Millar

In the context of a case study for an underground gold mine, the value generated by a schedule optimisation tool (SOT) is assessed. SOT is a software tool for underground mine planning that maximises the net present value (NPV) of a development and production schedule. A baseline study measures the NPV of a schedule generated by SOT from a sequence prepared by the site mine planners. Operational resource constraints and precedence constraints are adhered to by the schedule and NPV is evaluated with a financial model including revenues, costs and discount rate, as specified by the mine planner.The case study has several facets in addition to the baselining component. Scenarios were conducted that examined the degree of constraint on operational resources, the projected gold price and unit costs. Life-of-mine schedules subject to optimisation using SOT allowed for equitable comparisons.Haulage was identified as a dominant constraint for the mine. It was one of six operational resources that were used to constrain the optimisation of the mine schedule, with alternative levels for some of these constraints being identified so that their effects on the NPV could be studied. Alternative price projections for gold and different cost projections were identified and their effects on the optimised schedule examined. Price and cost scenarios that brought additional economic material into the schedule at various times in the mine life were considered in comparison to a scenario that assumed no additional economic material would become available.This case study illustrated that the use of a schedule optimisation tool to optimise mine schedules provides mine planners with an ability to perform a wide variety of analyses in a relatively short period of time. Such tools thereby support strategic decision-making that can add significant value to an orebody.The case study demonstrates that by fixing the set of development and production activities to be carried out before optimising the life-of-mine schedule, the mine planners can inadvertently set up a situation where the NPV would be progressively eroded in the last several years of the mine life. This clearly illustrates the need for schedule optimisation to be integrated with life-of-mine planning.CITATION:Fava, L, Maybee, B and Millar, D, 2012. Decision support for an underground gold mining operation - A case study using the schedule optimisation tool, in Proceedings Project Evaluation 2012 , pp 41-48 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

By P Myers, T Elkington, S Wonday

Sierra Rutile LimitedÆs (SRL) heavy mineral sand mining operation in Sierra Leone, West Africa, is embarking on a new phase of its life. After confronting many challenges during the 1990s and 2000s, SRL is embarking on a strategy of growth to recover maximum value from the mine over the rest of its life. Sophisticated linear programming techniques have been used to develop an optimum strategy for extracting SRLÆs many known deposits of economic grade, while considering options for expansion and for a variety of mining and processing methods and combinations. CITATION:Myers, P, Elkington, T and Wonday, S, 2012. Strategic optimisation at Sierra Rutile - A case study in maximising project value, in Proceedings Project Evaluation 2012 , pp 59-66 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

By S Watson, L Martinez

Mine projects are complex opportunities that demand a constant assessment of uncertainty, ie risk and upside potential. This is because the value of a mine project is typically influenced by many underlying economic and physical uncertainties, such as metal/mineral prices, metal/mineral grades, costs, schedules, quantities, and environmental issues, amongst others, which are not known with much certainty at the beginning of the project. But, is uncertainty an enemy or an ally of the mine planner/analyst? To answer this question, this paper first assesses and elaborates upon the general concept of uncertainty. It then looks at the different sources of uncertainty in a mining project, such as the orebody, costs and product price uncertainties, and their effect on the final project value. Next, a general?review?of current mine evaluation techniques highlighting their limitations when dealing with uncertainty is made. Finally, an extended evaluation and risk management framework that addresses the existing uncertainty in the (greenfield/brownfield) mine evaluation process is proposed. One important characteristic of this framework is that it uses and manages uncertainty in order to generate additional value to the project; this is done through operational and managerial flexibility, which allow mine planners to minimise/maximise project risk/upside-potential giving a more realistic estimate of the projectÆs market value - this is shown in practical and simple examples occurring at different stages of a mine project, such as exploration and operation. Final conclusions are provided at the end.CITATION:Martinez, L and Watson, S, 2012. Uncertainty - An important source of (additional) value for mine projects, in Proceedings Project Evaluation 2012 , pp 131-140 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

By W B. Edgar, S C. Dominy

High-nugget effect vein-gold systems are generally considered to be one of the most challenging of deposit types to evaluate and exploit. To potential investors and mining companies, they are viewed as high risk because of the associated uncertainties in the grade estimate and general paucity of Ore Reserves at production start-up. However, despite the well-known risks, these deposits often have a grade upside that makes them potentially attractive. The reporting of resource grade is of importance and perhaps even more so is the reporting of the associated uncertainty attached to the grade estimate. The use of the grade estimate supported by a grade range is recommended to achieve more complete and useful disclosure. The definition of the grade range can be somewhat subjective, ranging from opinion based estimates through to data-based estimates and geostatistical conditional simulation. Whichever method used, the over-riding issue must be the provision of enough data of appropriate quality and full disclosure to the public of relevant uncertainties.CITATION:Dominy, S C and Edgar, W B, 2012. Approaches to reporting grade uncertainty in high-nugget gold vein projects, in Proceedings Project Evaluation 2012 , pp 95-108 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

By A Chandra, P Guj

Only a few complex real options can be valued using closed-form equations, such as the Black and Scholes formula, because these algorithms are restrictive and prevent the construction of practical project evaluation models. Although a binomial lattice method paired with the ærisk-neutral probabilityÆ provides an easier and flexible modelling of exploration and mining projects, it has limitations when projects are complex, long-lived and influenced by the interplay of various market and private uncertainties. In order to overcome these limitations, modern decision tree software using dynamic programming capability can be used for real option valuations. This is a powerful computational tool in which the impact of various sources of uncertainties can be differentiated, so that the optimal decision path can be explicitly displayed visually. There has been significant academic controversy surrounding whether different real option (RO) valuation methods would lead to different real option values (ROV). This paper, using a realistic copper mining example, demonstrates that as long as the same degree of subjectivity and consistency are used in different real option valuation methods, they yield the same result. This conclusion is valid irrespective of whether the cash flow volatility generated by various sources of uncertainties is handled in an aggregated or in an explicit and differentiated manner. This paper compares two choices for an investor either to æbuy now and developÆ a project or to enter into a ætwo-year option to purchaseÆ after the proponents have developed it. It also shows how significantly different net after-tax operating cash flows may be generated by these different choices on the same underlying asset represented by the project. This is due to the difference in the amount and timing of the relevant capital investments affecting the depreciation and amortisation charges and as a consequence, the income tax paid. CITATION:Guj, P and Chandra, A, 2012. Real option valuation of mineral exploration/mining projects using decision trees - Differentiating market risk from private risk, in Proceedings Project Evaluation 2012 , pp 177-188 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

By G K. Robinson

Variations in many aspects of physical and chemical grade are often of concern to mining operations and mineral processing plants. In most circumstances these amounts of variation are predictable. At the time of planning new operations, we should be able to predict the amount of sampling and testing variation which our sampling devices, laboratory procedures and on-stream analysis devices will achieve. We should know how well our stockpiles, reclaimers and bins will homogenise material (or whether segregation will actually increase the amount of variation). We should be able to predict the amounts of variation that will occur on the important time or tonnage scales at the crucial p oints in our proposed operation. And once these amounts of variation are reliably known, mine planning will seem a little bit more like dealing with known knowns rather than like dealing with unknown unknowns.The first step towards quantifying amounts of variation for planned operations is to assess amounts of variation for existing operations. How many operations have estimates of amounts of variation in their databases? How often are people able to partition amounts of variation into amounts due to sampling error, amounts due to sample preparation, amounts due to assaying, and the amount of real variation in the stream of material?CITATION:Robinson, G K, 2012. Making sure that the amount of grade variation is a known known, in Proceedings Project Evaluation 2012 , pp 159-162 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

Risk management has become an essential tool for mining companies to ensure their projects are well-managed and profit expectations are achieved. Risk management has also become a mandatory corporate governance requirement in Australia for publicly listed companies and equally important to attract investors. This paper provides a brief overview of the essential tools needed to implement a practical risk management framework to comply with the internationally recognised ISO 31000:2009 risk management-principles and guidelines from the perspective of small or soon to be producing mining companies. To?successfully?deal with the unknown and to manage the opportunities and risks involved with a mining project requires a clear understanding of the basic risk management principles. These include how to develop a project risk register, how to develop a project risk treatment plan and how to manage and monitor project risks to take full advantage of the opportunities presented.The first step is to identify and fully appreciate the risks that face a mining project. There are many risk identification methods that can be used including checklists, brainstorming and hazard and operability (HAZOP) studies. These often lead to a telephone book full of risks which are near to impossible to manage. A risk library specifically designed?for mining?projects containing no more than 100 risks will cover the major showstoppers, is practical and can be readily implemented and successfully managed.A risk framework also needs to be established which is compatible with the companyÆs structure and objectives. Once each risk has been assessed in regard to consequence and likelihood and the risk control systems are in place they need to be assigned to the responsible manager. The extreme or high risks will require a risk treatment plan to be developed. Risks will change during the life cycle of a mining project. Hence, a reliable monitoring system is also required for compliance.CITATION:Jones, J A, 2012. Mine project risk management, in Proceedings Project Evaluation 2012 , pp 117-122 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

By A M. Ebbels, D Pratt

The current commodities super-cycle has seen an explosion in the number of mining projects demanding human resources throughout the world. The demand for key personnel currently far outweighs the international talent pool and will take several years to subside. A highly effective project team can be the difference between a successful project and a bad public relations exercise. Building an effective team and retaining the team members has become one of the major influencing factors for successful project development in the mining industry in the last decade.Increasingly, international teams are being established combining skill sets, subject matter experts, unique previous experiences and diverse cultures to deliver mining projects all around the world.This paper explores the characteristics of a highly effective team, the communication and geographic challenges and some potential pitfalls which influence the ability to form effective teams within the mining industry.CITATION:Ebbels, A M and Pratt, D, 2012. A great project team - Bringing together location and culture, in Proceedings Project Evaluation 2012 , pp 197-202 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

By J Gould, T Elkington

Mine operation strategies are commonly optimised with a net present value (NPV) maximisation objective. There are well known properties of a typical mining project optimised for NPV, including high production rates and declining cut-off grade schedules. In practice, however, frequently there are operations that diverge from such NPV-maximising properties. Although a range of reasons for this can be at play, one possible explanation is that operators intuitively adjust their strategies to compensate for the flaws inherent to NPV maximisation. In particular, NPV analysis does not reflect the benefits of managerial flexibility inherent in a mining plan. Real options valuation (ROV) is an alternative approach that addresses this issue. We compare the properties of NPV and ROV optimisation solutions generated for the same scenario. Our simple case study demonstrates that the presence of real operating options in the optimisation model not only entails increased project value as expected, but also tends to encourage lower processing capacity (with lower associated capital cost), higher cut-off grades and greater use of stockpiles.CITATION:Elkington, T and Gould, J, 2012. Real option value optimisation, in Proceedings Project Evaluation 2012 , pp 35-40 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

By S Shafiee, N Abbate

The evaluation of mining projects requires a methodology that will give flexibility and manage the existing uncertainty within the projects. The discount cash flow (DCF) and other traditional evaluation approaches, which are widely used in evaluating a significant number of mining projects, have simply assumed that the main variables remain constant in their evaluation; elements such as discounted rate, mine life, operating cost and production rate. The DCF ignores managementÆs flexibility to adapt and reforecast and revise decisions. Real options valuation (ROV) is one of the modern evaluation methodologies that provide a tool to adapt and revise mining projects under uncertainty and future variables movements. ROV brings more variables into the evaluation model compared to DCF and assumes them as uncertain and dependent. Finally, ROV provides a range of solutions that can assist in managing this flexibility.This paper endeavours to compare ROV and DCF for mining projects comprehensively and applies these two techniques in the model. The paper shows that ROV will be inclusive of extra value in mining projects due to variables not allowed for, or even ignored, when the DCF model alone is used. One of the significant advantages of the ROV method is being able to evaluate mining projects under different scenarios from the inception of the projects. Furthermore, ROV gives the ability to evaluate the mining project while allowing for abandonment, temporary suspension, or expanding the mining project. In other words, the ROV evaluation process creates an analytical environment, which allows for optimisation of the mining plan within the mining project, as well as the ability to change the capital structure dependant on existing circumstances over the life of the project. The ROV is a new evaluation method that can add value in mining project analysis and offers opportunities to amplify gains, or to mitigate losses. This paper also discusses some of the reluctance to use ROV instead of DCF in current project evaluation.CITATION:Shafiee, S and Abbate, N, 2012. Now, this is the time for mining companies to choose - Real option valuation or discount cash flow, in Proceedings Project Evaluation 2012 , pp 225-234 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

By P Card

Some project managers accept unsatisfactory economic evaluation modelling because they are unaware of what constitutes good practice. They tend to leave it to the evaluation specialist or others to decide. The AusIMM has published on its website a draft set of guidelines for technical economic evaluation which will allow these project managers to take control and demand worldÆs best practices.The style of the guidelines is described and the source of a worked spreadsheet example in Excel is given.Economic evaluation in project management is described. A simple test for the acceptance or rejection of evaluation work is offered. The nature of modelling and evaluation in each of the three study phases of concept, prefeasibility and final feasibility are described. Suggestions on the selection of specialists for each phase are given. The three levels of evaluation thinking are described, namely, modelling, valuation and evaluation. Finally the meaning of æfinancial analysisÆ is explained.The conclusion is that æthe role of an economic evaluation specialist is to create models and evaluations for the whole project team to readily understand and use: it is not to create models for his/her own useÆ.CITATION:Card, P, 2012. What project managers must demand from an economic evaluation!, in Proceedings Project Evaluation 2012 , pp 173-176 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

By G Lumley

PlannersÆ optimism (or maybe commercial necessity) means that most mine plans use equipment rates that are rarely achieved (Lumley and Beckman, 2009). This lack of understanding of what equipment actually moves is causing erroneous equipment forecasts, leading to incorrect mine development plans and economic evaluations. Compounding this problem is a downward trend in actual equipment performance in some areas. Consequently, the presentation of realistic mine plans that are actually achieved in practice is not a common occurrence. However, rational, fact-based mine planning is available to those who want it. Hundreds of millions of cycles of data from open cut mining equipment has been collected from mines around the world since 1992. This unique and highly valuable databank is growing at an exponential rate and is being used by a number of our big miners to support rational and fact-based decision-making. However, neither the use nor the appreciation of the value of this data is universal. There is a challenge to everyone in the mining industry - how do you access value from it? The databank was drilled into and the results analysed for, the Australasian Mining and Metallurgical Operating Practices (AMMOP) publication (Lumley, in press). For this paper the analysis has been extended to include interpretation of trends for draglines, shovels, excavators and trucks. It investigates trends between coal and non-coal mines and across geographic areas. It is known that mining equipment performance in most sections of the industry is falling. This paper attempts to quantify the fall and provide explanations. The trends are analysed to extract the reasons behind the changes and most importantly, what can be done about it.CITATION:Lumley, G, 2012. Understanding trends in performance of open cut mining equipment, in Proceedings Project Evaluation 2012 , pp 203-224 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

By G M. Jones, J Rademan

Debswana, owned by the Government of the Republic of Botswana (GRB) and De Beers in a 50:50 joint venture partnership, operates the Jwaneng diamond mine in Botswana - the most valuable diamond mine in the world. The mine provides between 60 - 70 per cent of DebswanaÆs earnings, and about 30 - 40 per cent of the GRBÆs income. In 2008, the company embarked on the Cut 8 Project - an open pit waste cut-back to expose more diamond bearing ore to sustain mine life by another six to seven years. This undertaking was much larger than previous cut-backs; it increased the waste stripping ratio threefold, increasing significantly the waste handling fleet of trucks, shovels and infrastructure, and impacted a large part of the materials handling plant which required replacement with new facilities. The project coincided with the beginning of the Global Financial Crisis (GFC) and a slowdown in the economy. Its $4 billion total life cost was billed as æthe largest private investment project in BotswanaÆ which produced heightened expectations amongst stakeholders that it would redress some of the issues brought about by the GFC and leave behind a legacy of jobs, increased opportunities for citizen owned business and improved social infrastructure.Most of the big project challenges were non-technical and ranged from dealing with various stakeholders?at?all levels, a 25 per cent currency depreciation of the Botswana Pula against the South African Rand, obtaining work permits for non-citizens in a job starved environment, managing construction to world class safety standards, managing the low productivity of construction workers and producing a viable legacy program that satisfied the GRB and stakeholders. Whilst most of these risks were identified in front end studies, the magnitudes were in many instances underestimated. Managing this uncertainty on Cut 8 can provide valuable lessons to other projects in a similar environment, or at least provide the information to indicate that these factors should be adequately provided for in the financial evaluation of a project in the form of budget, schedule, contingency or risk mitigation.CITATION:Jones, G M and J Rademan, 2012. Reliability of expert judgements and uncertainty assessments, in Proceedings Project Evaluation 2012 , pp 109-116 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

By T Y. Dube

In this paper current net present value (NPV) based mine valuation techniques that take into account market and private risk are discussed and analysed. Potential pitfalls that arise from the application of a portfolio, market or commodity based risk metric to a mining project are identified. An alternative non-simulative framework for quantifying and factoring market and private risk in NPV calculations is proposed and then applied to a hypothetical case study in an attempt to overcome identified pitfalls. Mathematical proof that a static discounted cash flow (DCF) calculation can underestimate or overestimate mine NPV is presented, the conditions for each are outlined and the degree of underestimation defined.CITATION:Dube, T Y, 2012. How the use of market-based risk metrics can undervalue good mining projects and overvalue poor ones, in Proceedings Project Evaluation 2012 , pp 29-34 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

By D Jeffery, R Whittering, G Lane

Most aspects of process design are best addressed via bench scale or pilot plant scale test work. However, as experience is gained, fundamental or indicative data can provide more than adequate information to manage the risk associated with some process aspects of concentrator design.Historical precedence exists where minimal design test work has resulted in successful projects. On many occasions benchmarking, sometimes supported by fundamental data such as mineralogy, has been used to successfully develop effective process plant outcomes. Of course, this style of approach is most common with æfast trackÆ projects and often comes with the usual surprises that result from inadequate geometallurgy to define the project cash flow.This paper explores the risks and opportunities associated with the various facets of process development and design for a base metals concentrator. The paper is intended to provide guidance to project managers rather than address the technical aspects of process engineering.CITATION:Lane, G, Whittering, R and Jeffery, D, 2012. Benchmarking versus test work - How should you manage process risk?, in Proceedings Project Evaluation 2012 , pp 49-52 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

By T Schrimpf, I Bryan

The life cycle of a mining project begins with initial regional exploration and ends with mine closure and rehabilitation. Between resource definition and the commencement of mine construction is the study phase. In this phase technical concepts and processes are defined, evaluated and assessed with the aim of establishing whether the deposit is economically feasible. The study phase usually involves various steps from a concept/scoping study to prefeasibility and ultimately definitive feasibility study. The complete study phase can take several years. Although the costs for studies are low in comparison to actual construction and operating costs of a mining project, they are significant especially for junior exploration and mining companies advancing projects to the point of being funded.The studies aim to determine selected parameters for the project, eg mining and processing methods, operating strategy, etc and provide a roadmap for project development ahead. Although mining studies are of the utmost importance for the mining project and the project owner, they are usually carried out using a conventional engineering approach: the consultant or design engineer works to a defined scope of work. The resulting design might be based on good engineering, but might often also fail to provide the solution for the project owner that delivers the best shareholder value. An alternative to this more traditional approach to project evaluation is what we have termed a value engineering approach. Value engineering is a creative, organised effort, which in the case of a mining study analyses the requirements of the study for the purpose of achieving the essential outcomes with the highest shareholder value. The outcome of a study is a concept that delivers the highest achievable value of the resource project and shows the way ahead to realise this value. Through a group investigation by experienced, multi-disciplinary teams the value of the resource is improved through the study of alternative options, methods and processes. The scope of the study is not limited to a narrowly defined engineering scope, but to the creation of value.The study commences with the identification of key value drivers and risks, based on the available information (drill data, geotechnical data, metallurgical test work, etc). This enables the quantification of key uncertainties, risks and value adding opportunities. Study efforts concentrate on key value drivers and are not unnecessarily spent on side issues. This approach can significantly reduce the time frame and costs for the study phase.This paper describes in more detail RMDSTEMÆs value engineering approach to mining studies and illustrates it with examples and case studies.CITATION:Schrimpf, T and Bryan, I, 2012. The application of value engineering principles to mining studies, in Proceedings Project Evaluation 2012 , pp 163-170 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

By B Olsson, B Reynolds, R Norman

An unprecedented growth in demand for coal exports has placed pressure on multi-user coal chains to guarantee that their capacity expansion projects will meet the required demand. These projects, however, are taking place in an increasingly complex commercial and technical environment - competing rail and coal terminal service providers as well as a myriad of competing mine operators, all needing to operate in an increasingly integrated manner to get the most out of expensive shared assets.Increasing system complexity and integration has driven the need for more holistic and sophisticated analysis tools. The capacity of coal chain subsystems, such as mine, rail and port, can no longer be determined effectively in isolation. Understanding the nature of the interactions between these subsystems, their sensitivity to uncertainty and the resultant capacity of the integrated system is the key to both maximising value and minimising risk.Recently, TSG has worked closely together with the Integrated Logistics Company and a number of key stakeholders in the Dalrymple Bay Coal Chain to develop independent system master plans. These master plans have provided a quantitative and rational assessment of coal chain capacity in its current state and a prediction of its capacity once a pipeline of committed capacity improvements is in place. This paper provides an overview of the study and a comprehensive guide to the process required to effectively achieve valuable strategic insights in a challenging multi-user stakeholder environment.CITATION:Reynolds, B, Olsson, B and Norman, R, 2012. Using independent system simulation to mitigate risk in the Dalrymple Bay Coal Chain, in Proceedings Project Evaluation 2012 , pp 77-84 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

By S Coward, J Vann, R Wolff, S Jackson, S Moayer, A Bye

Uncertainty about the future and orebody should significantly impact evaluation of mining projects. Scenario planning, widely used in other industries, for example in the petroleum industry, can provide organisations with an opportunity to explore the consequences of uncertainty on their future plans. By developing plausible scenarios, scenario planning assists decision makers by allowing them to make systematic and possibly effective decisions for the future. This paper reviews existing mine project evaluation in the context of a new framework called scenario-based project evaluation (SBPE) (Vann et al , 2012) that addresses many shortcomings of existing approaches. SBPE uses conditional simulations (CS) models as inputs which are evaluated against future alternative project pathways (æalternativesÆ). These alternatives are evaluated using multiple plausible images of the deposit (CS realisations) which capture realistic variability and as an ensemble, map uncertainty of various orebody attributes at fine scale. The alternatives can involve different mining, stockpiling, blending and processing strategies. The ultimate output is a (stochastic) set of cash flows for each alternative from which financial measures, such as NPV, can be derived. Alternatives can then be explored in the presence of against external scenarios such as changes in prices, costs, and taxation. The obvious problem with such data rich results is knowing which scenarios or group of scenarios are optimal.An innovative approach to robust stochastic optimisation (RSO) suited to the SBPE framework is presented here for the first time. This approach to RSO aims to deal with the large number of alternatives generated from SPBE. The goal of applying the RSO approach to SBPE is to identify robust strategic alternatives (project configurations) which have the flexibility to deal with variability and uncertainty of geological and processing inputs such as density, grade and process performance. By applying the proposed RSO method, it is possible to deal with uncertainty and identify the best project configuration in the face of a large number of envisaged scenarios. A case study is provided, in which we have tested the application of the proposed method and compared the result with conventional methods. An important conclusion from this research is that selecting the value of the penalty coefficients in the RSO approach proposed is (as is all optimisation) an exercise of trade-offs; a higher net present value (NPV) is generally associated with a higher risk and a lower risk is associated with a lower NPV. Indeed, this is a strong argument for considering the RSO approach outlined here over more conventional approaches.CITATION:Moayer, S, Vann, J, Coward, S, Jackson, S, Bye, A and Wolff, R, 2012. An innovative approach to robust optimisation for scenario-based mineral project evaluation, in Proceedings Project Evaluation 2012 , pp 141-148 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012