The quantification of grade uncertainty, and associated risk, and their influence on pit optimisation for the Sadiola deep sulphide prefeasability project

Abstract

In order to quantify the uncertainty in the grade estimate for the Sadiola Deep Sulphide Prefeasibility Project a conditional simulation model was generated using Direct Block Simulation methodology. Compared to conventional Sequential Gaussian Simulation, the Direct Block Simulation algorithm produced a reliable model in significantly less time, lending its application to a production environment. Through application of a mining transfer function, risk pits were generated for comparison with the Deep Sulphide Prefeasibility pit. The results of this study revealed that the prefeasibility pit is optimal at the applied gold price and cost parameters, and that the risk of not achieving the project grade profile is low. Should the gold price increase, or the operating costs of the project decrease significantly, the Deep Sulphide reserve tonnage would realise significant upside potential. The potential for using the simulation model coefficient of variation to improve the classification of the resource has been highlighted. This exercise could allow significant saving of feasibility drilling capital.