Statistical and Probabilistic Closure Cost Estimating

Abstract

This paper describes a statistically based framework for determining mine closure costs. A range of future potential mine closure scenariosare established and described using a decision tree approach. This allows for consideration of a large number of combinations of closure elements for the various mine facilities. The decision tree is used to establish a cost probability curve that in turn provides for determining closure costs at different levels of confidence. It is also used to identify the high risk and high cost elements. Monte Carlo techniques are also employed to determine the cost variability of individual mine closure scenarios such as the expected cost or the most likely closure scenario. This approach avoids the difficulty of trying to establish a single closure cost estimate and provides closure cost and probability information that can be used in feasibility evaluations, budgeting, reserve setting and also for the prioritization and management of high cost risks.