Decision-making within geochemical exploration data based on spatial uncertainty – A new insight and a futuristic review
Behnam Sadeghi, David Cohen
Abstract
In mineral prospectivity mapping, limitations in the density of geochemical sampling that can be collected across a region may generate the need for interpolation of data between sampling locations, with associated errors in the estimates. This study investigates quantification and modeling of this spatial uncertainty based on multivariate statistical quantile models of element concentrations in low-density till sampling across Sweden and the high-density soil geochemical atlas sampling of Cyprus. Sequential Gaussian simulation was applied to both datasets, with the dissimilarity between a large number of realizations quantified using a Euclidean distance-based model and the relevant spatial uncertainty. Using a P50-spatial uncertainty efficiency frontier plot, the classes with the highest P50 and lowest spatial uncertainty are compared with the distribution of known base metal mineral deposits.