Stochastic Simulation of Geology for Uncertainty Analysis

Sustainable development of mineral resources is based on a spatial model of the orebody that is only partly known from exploration drilling and associated geological interpretations. As a result, orebody models generated from the available information are uncertain and require the use of stochastic conditional simulation technique. This paper considers three methods for simulating orebody geology: (1) pluri-Gaussian simulation that limits the allowable contacts between the various units; (2) sequential indicator simulation using indicator kriging; and (3) an experimental multiple-point approach that captures some higher-order spatial statistics. The data requirements of the methods, how to meet them in mining applications, and performance characteristics are discussed. The application of these methods in a hypothetical deposit consisting of three geological units provides a comparison and illustrates the advantages of the different simulation approaches.