Abstract

Traditional mine planning based on block models built with interpolation techniques such as kriging does not take into account the uncertainty associated with the estimates. These models are inadequate for short-range mine planning. In contrast, conditionally simulated models reproduce the actual variability (histogram) and spatial continuity (variogram) of the attributes of interest. Conditional simulation can be used to address the problem of measuring the uncertainty associated with an estimate. This paper outlines how the sequential Gaussian conditional simulation algorithm can be used to assess uncertainty of grade estimates and also illustrates how simulated models can be incorporated into mine planning and scheduling. A case study demonstrates the efficiency of the method in assessing risk associated with geological and engineering variables.

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