Evaluation Of Mining Projects Research Articles

A KNETSCH PROPOSITION AND A DUE PROCESS FOR THE EVALUATION OF MINING PROJECTS IN ECOLOGICALLY SENSITIVE AREAS: AN ILLUSTRATION THROUGH TWO AUSTRALIAN CASE STUDIES

Drawn on some Knetsch observations, this paper illustrates a due process for the economic evaluation of mining projects that impact sensitive and irreversible ecological assets. Towards this end, two case studies of coal mining projects in Australia are considered — one on the Liverpool Plains in New South Wales and the other on the Galilee Basin in Central Queensland. The adverse environmental and social externalities of these projects are well known — especially the impacts on the Gunnedah and the Great Artesian Basins. Notwithstanding these impacts, which are exceedingly difficult to value, private financial analyses demonstrate significant revenue gains. Mining firms find such gains difficult to ignore. Nevertheless, economic analyses illustrate that the net benefits to Australia are possibly absent even without accounting for the costs of environmental social externalities. Given that the property rights of the mineral reserves are vested with the State, the Resource Rent Tax (RRT) becomes a legitimate fiscal policy tool. The paper argues that the assessment of mining decisions must account for the depreciation of the Mineral asset. When this depreciation is measured alongside the Hartwick–Rule, the mining projects demonstrate monetary viability only when the RRT is enforced and is invested in its entirety on options that generate annual returns in excess of 3% to 4%. If recognized, the costs of environmental and social externalities could readily wipe out this, and for that matter any, monetary viability owing to the irreversible nature of the natural social endowments.

Evaluation of mining projects subjected to economic uncertainties using the Monte Carlo simulation and the binomial tree method: Case study in a phosphate mine in Egypt

Mining project evaluation is a very complex process and time-consuming task. Any mining project passes through several study stages, like conceptual, preliminary feasibility, and feasibility studies, using a systematic and standardized approach. These studies allow investors to evaluate the exploitations alternatives according to economic and technical criteria to make a better decision. This research aims to study a model for investment risk analysis developed for the case study of “Abu Tartur mining project, Egypt.” Abu Tartur plateau is rich in phosphate rock, turned into phosphoric acid and fertilizers. This study used site-specific data that has been taken from the literature to build evaluation models using the Monte Carlo Simulation (MCS) and the Binomial Decision Tree (BDT) methods. The Discounted Cash Flow (DCF) is considered a benchmark method for all other evaluation methods. The MCS method uses a set of parameters that, in some cases, will give a higher NPV of the project and some others with lower values, but this depends on the probability of the input parameters. The developed evaluation models allowed a specific range of values, with confidence intervals as the MCS model. The advantage of using a probabilistic approach helps in the decisional phase, allowing for a more precise overview of the variability of the final economic value of the mine. Deterministic methods, like the DCF method, offer a solution that is limited to uncertainty analysis.

A New Ore Grade Estimation Using Combine Machine Learning Algorithms

Accurate prediction of mineral grades is a fundamental step in mineral exploration and resource estimation, which plays a significant role in the economic evaluation of mining projects. Currently available methods are based either on geometrical approaches or geostatistical techniques that often considers the grade as a regionalised variable. In this paper, we propose a grade estimation technique that combines multilayer feed-forward neural network (NN) and k-nearest neighbour (kNN) models to estimate the grade distribution within a mineral deposit. The models were created by using the available geological information (lithology and alteration) as well as sample locations (easting, northing, and altitude) obtained from the drill hole data. The proposed approach explicitly maintains pattern recognition over the geological features and the chemical composition (mineral grade) of the data. Prior to the estimation of grades, rock types and alterations were predicted at unsampled locations using the kNN algorithm. The presented case study demonstrates that the proposed approach can predict the grades on a test dataset with a mean absolute error (MAE) of 0.507 and R2=0.528, whereas the traditional model, which only uses the coordinates of sample points as an input, yielded an MAE value of 0.862 and R2=0.112. The proposed approach is promising and could be an alternative way to estimates grades in a similar modelling tasks.

Revaluation of alluvial deposits residual reserves of boulder chrome ores of the Saranovsky ore field

Relevance of the work. After the collapse of the USSR, local ferroalloy industry experienced a deficit in certain types of mineral raw materials, in particular in chromium ores. In Perm Krai, in the vicinity of the village Sarany, medium and small-scale deposits of primary magmatic and fragmental slop wash ore of high iron content and alumina are known, previously used only as refractory raw materials. In the 1990–2000s, technologies for producing commercial and conversion ferrochrome with low chromium content (“charge-chromium”) using chromium ores of the Ural region, including ores from deposits of the Saranovsky group, were developed and introduced on an industrial scale. All this entailed the need for geological and economic revaluation of the reserves of known deposits, including placers of wash ores partially affected by mining operations of previous years. The revaluation included not only the residual natural reserves of deposits, but the technogenic formations in their areas containing underextracted ore round stones as well. Currently, the project for the development of boulder placers is being successfully implemented. The experience gained may be of interest in reassessing the residual reserves of objects of scarce types of mineral raw materials characterized by a complex "natural-technogenic" structure. Purpose of the work: to summarize the experience of joint revaluation of residual natural reserves and technogenic formations on the areas of placer deposits of boulder chrome ores aimed at ensuring the maximum completeness of excavation of scarce raw materials. Method and methodology of the work carried out. The main idea of the work is to jointly reassess the industrial importance of the residual reserves of boulder chrome ores contained in natural and man-made formations in placer areas. Given the relatively simple mining and geological conditions and small volumes of annual production, the criterion of “minimum industrial output of ore boulders”, which achieves equality of the recoverable value of mineral raw materials to the operating costs of obtaining marketable products, is proposed to be applied to the residual reserves of the placer, and not to individual geological blocks. This approach obliges the subsoil user to conduct continuous mining of the remaining reserves, to involve in the industrial development reserves of low-productive geological blocks, including those represented by technogenic formations, the average yield of ore boulders from which, as a rule, is lower than the estimated industrial minimum. The rational choice of placers that are simultaneously mined is justified by economic indicators used in the evaluation of mining projects (net present value, profitability index, budget efficiency, etc.), taking into account the “individual” characteristics of individual deposits. The proposed approach to involving in the development of reserves of low-productive areas (including technogenic formations) can be implemented not only at the level of individual deposits, but at the level of a group of “converging” differently productive placers as well, when both highly productive and “poor” placers are being developed, the reserves of which in the traditional assessment are classified only as off-balance sheet (potentially economic). Results of the works. The description is given of methodological approaches to the revaluation and rational use of residual reserves of boulder chrome ores disrupted by mining operations of previous years. The experience gained can be used to evaluate other mining facilities that contain natural and technogenic formations of different productivity on their area.

Comparison between traditional project appraisal methods and uncertainty analysis applied to mining planning

Abstract Long-term mining planning is a complex process which involves a large number of variables and uncertainties. Traditional discount cash flow (DCF) is usually used in the evaluation of mining projects. DCF includes net present value (NPV), internal rate of return (IRR), and profitability index (PI). A sensitivity analysis is usually carried out to evaluate the impact of the main variables on the project. Another way to measure uncertainties is through the Monte Carlo simulation (MCS). The objective of this study is to evaluate and compare the DCF methods and measure uncertainties through sensitivity analysis and MCS in the evaluation of mine sequencing. A case study of a phosphate mine project was used to chart the comparative study. In the results, NPV and uncertainty analysis through MCS were more consistent.

Incorporating stochastic correlations into mining project evaluation using the Jacobi process

Uncertainty is an important phenomenon in mine project evaluation. Recovery, grade, commodity price, discount rate, and operating costs are highly uncertain variables. Given that uncertainties cannot be fully eliminated, mining companies focus on assessing risks associated with uncertainties. Mining projects generally encompass 10–50 years, and the evolution of uncertain parameters over this long time period is also uncertain. Since the future cannot be predicted, one way to deal with uncertainty is to create probable images of reality through simulation. When simulating multiple uncertain variables over time, an immediate problem is how to handle correlations among uncertain variables because the correlations themselves are uncertain variables. In this paper, the Jacobi process is used to treat the correlations stochastically. A case study was implemented in a mine project evaluation (e.g., net present value and option pricing), in which the gold prices and the US interest rates were considered as correlated uncertain variables. The correlations among uncertain variables significantly affected the value of the mining project. The Jacobi process can be used as a tool to increase the performance of mine project evaluation.

Cost-Benefit Evaluation of Mining Projects

This article describes the cost–benefit analysis of mining projects. Following a general introduction, the central part discusses six contentious topics: the community of interest, valuing the environment, second-round effects, market modelling, estimating key mining data and treatment of risks. The penultimate section briefly discusses dealing with some special government requirements. The article concludes that the cost–benefit analysis approach is systematic and comprehensive. Where uncertainty exists, the weights attributed to unquantified impacts should be conceived within a cost–benefit analysis framework, rather than out of the subjective thoughts of decision-makers.

Methodology for selection of samples from borehole probe for technological characterization of iron ore

The risks in the evaluation of mining projects are directly related to the probability of errors in the estimates, and, as the estimates are based on sampling results, this activity must be performed in a careful and planned way, to prevent surprises at the beginning of operation. To validate the representativeness of the borehole samples selected for the mineral processing studies, the geological resources evaluation team proposed a methodology based on the utilization of statistical analyses that, beyond considering the spatial distribution of the samples in the deposit, also assessed if they are representative of the populations under investigation. With this data, the geologist is able to make a fast analysis of the sampling's representativeness.

A numerical study for a mining project using real options valuation under commodity price uncertainty

Commodity price is an important factor for mining companies, as price volatility is a key parameter for mining project evaluation and investment decision making. The conventional discounted cash flow (DCF) methods are broadly used for mining project valuations, however, based on commodity price uncertainty and operational flexibilities, it is difficult and often inappropriate to determine mining project values through traditional DCF methods alone. In order to more accurately evaluate the economic viability of a mining project, the commodity price and its inherent volatility should be modelled appropriately and incorporated into the evaluation process. As a consequence, researchers and practitioners continue to develop and introduce real options valuation (ROV) methods for mining project evaluations under commodity price uncertainty, incorporating continuous time stochastic models. Although the concept of ROV arose a few decades ago, most of the models that have been developed to-date are generally limited to theoretical research and academia and consequently, the application of ROV methods remains poorly understood and often not used in mining project valuations. Analytical and numerical solutions derived through the application of ROV methods are rarely found in practice due to the complexity associated with solving the partial differential equations (PDE), which are dependent on several conditions and parameters. As a consequence, it may not generally be applicable to evaluate mining projects under all project-specific circumstances. Therefore, the greatest challenge to ROV modelling is in finding numerically explicit project values. This paper contributes towards the further development of known theoretical work and enhances an approach to approximating explicit numerical project values. Based on this work, it is possible to formulate more complex PDEs under additional uncertainties attached to the project and to approximate its numerical value or value ranges. To ensure the project is profitable and to reduce commodity price uncertainty, delta hedging and futures contracts have been used as options for deriving the PDE. Moreover, a new parameter for taxes has been incorporated within the PDE. This new PDE has been utilised to approximate the numerical values of a mining project considering a hypothetical gold mine as a case study. The explicit finite difference method (FDM) and MatLab software have been used and implemented to solve this PDE and to determine the numerical project values considering the available options associated with a mining project. In addition, commodity price volatility has been determined from historical data, and has again revealed price volatility as having a significant impact on mining project values.

Determination of the effect of economic uncertainties on mining project evaluation using Real Option Valuation

Value of a mine project is typically influenced by several kinds of uncertainties. Therefore, it is necessary that the mining uncertainties be recognised at the initial stage and then the evaluation process be carried out. Obviously, the economic uncertainties are the most important parameters, which can affect the evaluation process. Selecting the most reliable method for evaluating a mining project is another knot. The results of conventional mining project evaluation methods such as Discounted Cash Flow (DCF) are conservative and these methods cannot represent the real value of mining projects. To solve this problem, it is necessary to use more accurate techniques such as Real Option Valuation (ROV). This research uses the DCF and ROV methods to compute the Net Present Value (NPV) of the Cayeli copper mine under uncertainties of operating costs and metal price. It is concluded that the NPV, which is calculated by ROV, is 40% greater than DCF.

New approach for estimating total mining costs in surface coal mines

Accurate cost estimation is a critical component of mining project evaluation to determine whether the proposed project is clearly feasible, doubtfully feasible or clearly uneconomic. At the beginning of the process, it is very difficult for project evaluators to find reliable relevant data that can be used for all phases of the cost estimation. This paper provides an overview of published work on mining cost estimation methods, data sources and available software. It also introduces the concept of indices for different components of mining projects, discusses their historical movements, and then it compares mining cost indices in the USA, Canada and Australia. It also introduces a new econometric model for estimating the operating cost and capital cost of a coal mining project. The total operating cost and capital cost of mining are calculated by using the proposed econometric model and verified by comparing the outputs with CostMine data and Sherpa software outputs for a surface coal mine. The model shows that the capital cost and production rate have a negative effect on the operating cost, while the deposit average thickness and stripping ratio have a positive effect.

Determination of the effect of operating cost uncertainty on mining project evaluation

Mining projects are complex businesses that demand constant risk assessment. This is because several kinds of uncertainties influence the value of a mine project, typically. These uncertainties may be classified as exploration uncertainties, economic uncertainties and engineering uncertainties. The evaluation of a mine project under these uncertainties is a complicated job, which may lead to making a wrong decision by managers and stockholders. Therefore, at first, the engineers must recognize the mining uncertainties before carrying out the project evaluation. The economic uncertainties are the most important factors, which may affect the project evaluation. Among the mentioned uncertainties, the operating cost uncertainty is an important and effective factor, which is ignored to a certain extent.This research uses the binomial tree technique to compute the net present value of the Cayeli copper mine under three scenarios: (1) assuming certainty for both price and operating costs, (2) assuming uncertainty for metal price and certainty for operating costs and (3) assuming uncertainty for both price and operating costs. It is concluded that the mine evaluation suggests greater net present value when uncertainty is considered for both price and operating costs.

Pre-mining water quality prediction from non-weathered sulphide ores along the Ashanti metallogenic belt in Ghana using Acid-Base accounting procedure

The prediction of pre-mining water quality from non-weathered sulphide ores using the Acid-Base accounting (ABA) procedure was studied at the Anglogold-Ashanti, Obuasi mine and located on the Ashanti metallogenic belt in Ghana. The purpose of the study was to establish database for use during preliminary mining project evaluation, mining project permitting, and tailings waste management planning and implementation. Total Sulphur (TS) was determined by hightemperature furnace combustion using the LECO sulphur analyzer, while carbonate was determined by gravimetric method. Average TS % and Neutralization Potential (NP) due to calcium carbonate were 1.46% and 4.34 kg CaCO3/ton respectively. The average TS% multiplied by the constant 31.25 yielded Maximum Potential Acidity (MPA) value of 45.63 kg CaCO3/ton. Also, Net Neutralization Potential (NNP), defined by NNP=NP-MPA, yielded the value -41.29 kg CaCO3/ton and NP: MPA ratio of 0.095. Multiple regression statistics on NP and MPA gave Rsquare value as 0.0005 and indicated a poor predictive neutralization model. From the NNP and NP: MPA values, it was concluded that the non-weathered sulphide ores at the AnglogoldAshanti, Obuasi mine are likely to generate high acidic waters. Adequate alkaline amendment is therefore required during ore treatment.

Risk quantification using qualitative tools

Measuring risk and including it within the evaluation of mining projects has the potential to facilitate better decision-making practices. By quantifying the risks associated with a particular mining scenario, these uncertain components can influence the project's value. Unfortunately, many of the risk factors that influence a mining project are qualitative in nature, and do not easily lend themselves to numerical evaluation. This paper looks at some of the misapplications of quantitative risk analysis tools in the highly uncertain mining industry. It begins with a review of the progression of valuation techniques that have been used in the mining industry, followed by a look at some of the issues with performing a risk-based evaluation. Using a case study, qualitative risk analysis tools are used to show how these quantitative issues can be alleviated, closing with a brief discussion about possible future research directions.