Multivariate geostatistical simulation of a nickel laterite deposit

There are many variables to consider in the evaluation of nickel laterite deposits including the concentrations of nickel, iron, silica, and magnesia. These variables show complex relationships with each other such as mineralogical constraints, non-linear correlation, and heteroscedasticity. The complex multivariate relationship between the variables cannot be reproduced by conventional Gaussian or indicator geostatistical techniques. We introduce the stepwise conditional transformation method as a pre- and post-processing multivariate transform for the stochastic simulation of a nickel laterite deposit. Transformed data are multiGaussian and independent at h = 0; thus, cosimulation can be avoided after verification that variables are independent at all lag distances. Back transformation restores the features of the input multivariate distribution to the simulated realizations. The complex multivariate correlations are reproduced and sensitivity issues are addressed.