Probabilistic Modeling of Lateritic Nickel Mineral Resources

Abstract

Lateritic nickel deposits exhibit complex weathering-driven geometries, strong vertical variability, and complex multivariate geochemical relationships. These characteristics challenge conventional deterministic resource modeling. This paper presents a unified probabilistic workflow for lateritic nickel mineral resource modeling that integrates lithology and grade simulation within a consistent geostatistical framework. The methodology combines unfolding, plurigaussian simulation, multivariate imputation of incomplete datasets, projection pursuit multivariate transformation (PPMT) for decorrelation, and conditional simulation using the Turning Bands algorithm. Application to an Indonesian lateritic nickel deposit demonstrates reproduction of lithological proportions, spatial continuity, marginal distributions, and complex multivariate relationships. The proposed workflow enables explicit quantification of geological and grade uncertainty, providing a basis for uncertainty assessment in recoverable resource estimation and supporting downstream applications such as resource classification and drillhole spacing analysis.