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.
