Application of Conditional Simulation to Quantify Uncertainty and to Classify a Diamond Deflation Deposit

Since the early 1900’s diamonds have been known to occur in aeolian placers in south western Namibia. At Namdeb’s Elizabeth Bay Mine diamonds are extracted from the fine to coarse grit layers in a sequence of stratigraphic horizons formed during periods of vigorous wind action. Significant capital expenditure is required to extend the life of mine at Elizabeth Bay and, as this is an inherently high-risk deposit, a sound understanding of the risks associated with the resource estimates is required. Various methods were evaluated to quantify the uncertainty of the thickness estimates and to facilitate classification according to the SAMREC guidelines. The thickness of the resource has a significant impact on the mining method as well as volume calculations. This investigation involves the use of conditional simulation of thickness to derive a method for classifying the resource. The simulations were used to construct block conditional distribution functions and evaluate a number of uncertainty measures, including conditional variance, conditional coefficient of variation, interquartile range and probability interval. A method employing conditional simulation to assess the efficiency of sample spacing is briefly presented. The approaches using coefficient of variation calculations provide promising results that enable classification of uncertainty related to the thickness of the Elizabeth Bay resource.