Open Collections

Statistical and probabilistic closure cost estimating

Tailings and Mine Waste Conference (2011 : Vancouver, B.C.); University of British Columbia. Norman B. Keevil Institute of Mining Engineering

This paper describes a statistically based framework for determining mine closure costs. A range of future potential mine closure scenarios are 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. [All papers were considered for technical and language appropriateness by the organizing committee.]

Text

2011-10-18

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/38038

Unreviewed

http://creativecommons.org/licenses/by-nc-nd/4.0/