This paper is concerned with the application of a probabilistic approach to the risk assessment of mining projects.
In current practice, sensitivity analysis is the most commonly used deterministic approach of accounting for the uncertainties involved in mining project evaluation, while Monte Carlo simulation is considered to be the best probabilistic method available for the same purpose. The methodology of the approach proposed in this paper is as simple as that of sensitivity analysis. However, the results obtained can be more comprehensive than those obtained from Monte Carlo simulation.
Various important statistical features, such as correlation and skewness, of the basic random parameters can be easily taken into account by the proposed approach. Example studies are demonstrated. Lotus 123 was employed for the associated probabilistic calculations.