Stochastic Mine Planning—Example and Value from Integrating Long- and Short-Term Mine Planning Through Simulated Grade Control, Sunrise Dam, Western Australia

Abstract

A new multistage stochastic mine production scheduling approach is developed and tested in a large operating gold mine. The proposed approach takes short-scale orebody information in the form of grade control data into account. As simulated orebodies used in stochastic long-term mine planning are based on sparse exploration data and while grade control data are unavailable at the time of production scheduling, the short-scale information is first simulated stochastically and then serves as input to the optimisation process. Stage 1 of the approach generates high density future grade control data for incorporation into the production scheduling process based on sequential co-simulation and pseudo cross-variograms between exploration data and grade control in previously mined out parts of a deposit. In Stage 2, the technique of conditional simulation by successive residuals enables pre-existing simulated orebody models to be updated using the simulated future grade control information. Stage is based on a stochastic programming mine scheduling formulation that handles multiple simulated orebody models from Stage 2 and accommodates both maximising Net Present Value (NPV) and minimising deviations from production targets. Stage 4 includes quantification of risk in the produced schedules generated, comparison of schedules and reporting. The application at a large operating gold mine demonstrates that the proposed approach is practical and adds value to the operation. The approach is shown to deliver additional ore (3.6 Mt more) and metal (2.6 million grams) which matches the mined reconciliations and results in a cumulative NPV which is on average A$7.7 M higher than that of a stochastic schedule without the simulated grade control data and substantially higher (about 30%) compared to the NPV from the actual schedule of the mine.