The impact of variability and correlation of selected geological parameters on the economic assessment of bituminous coal deposits with use of non-parametric bootstrap and copula-based Monte Carlo simulation

Abstract

This paper presents an assessment of the impact of variability and interdependencies of selected deposit parameters on the net present value (NPV) and internal rate of return (IRR). The subjects of the analyses were three economically viable seams at one of the bituminous coal deposits in Poland. The source of information was the geological model and operational data of the mine “X”. The simulation was developed based on non-parametric bootstrapping, where the influence of coal quality parameters, seam thickness, spatial density of coal, and waste rock derived from coal partings, floor cutting and dinting, and roof falls, was tested.The interdependencies of geological and mining parameters were replicated in a simulation model using Gaussian and empirical copulas. In the model, the relationship between the amount of total waste rock and operating costs was associated with the use of elaborate mathematical formulas. Economic appraisal was based on an income approach, using the free cash flow for the firm (FCFF) analysis and discounting process.Based on the Gaussian copula, in the X-1 and X-2 seams, the average NPV differences achieved were a maximum of 39%. In the case of IRR, the mean difference did not exceed 3.6% points (pp). The quantified spread between the correlated and uncorrelated average values of NPV was at most 45% and 4.8 pp for IRR. Empirical copula limits the range of variation of input and output parameters, resulting in different values for the average NPV, at a maximum of 11.8%, and IRR, 2.4 pp.If the IRR reflects the level of expected return of investment, it can be stated that the additional risk premium resulting from the volatility and correlation of analysed deposits parameters of bituminous coal should be relatively low and less than 2.4 pp in similar cases. The analyses also revealed that the amount of available geological information is of secondary importance in the valuation process, as it does not negatively affect the regularity and symmetry of predicted outcomes.