Geostatistical Simulation of Geochemical Compositions in the Presence of Multiple Geological Units: Application to Mineral Resource Evaluation

An accurate prediction of benefit in ore deposits with heterogeneous spatial variations requires the definition of geological domains that differentiate the types of mineralogy, alteration, and lithology, as well as the prediction of full mineral and geochemical compositions within each modeled domain and across boundaries between different domains. This paper proposes and compares various approaches (different combinations of log-ratio transformation, Gaussian and flow anamorphosis, and deterministic or probabilistic geological models) for geostatistical simulation of geochemical compositions in the presence of several geological domains. Different approaches are illustrated through an application to a nickel–cobalt laterite deposit located in Western Australia. Four rock types (ferruginous, smectite, saprolite, and ultramafic) are considered to define compositionally homogeneous domains. Geochemical compositions are comprised of six different components of interest (Fe, Al, Mg, Ni, Co, and Filler). The results suggest that the flow anamorphosis is a vital element for geostatistical modeling of geochemical composition due to its invariance properties and capability for reproducing complex patterns in input data, including: presence of outliers, presence of several populations (due to the presence of several geological domains), nonlinearity, and heteroscedasticity.