Assessing risk in grade-tonnage curves in a complex copper deposit, northern Brazil, based on an efficient joint

Risk quantification in grade-tonnage curves is critical for capital investment in mining projects and can be obtained through geostatistical simulations of orebodies. A practical difficulty may arise in multi-element deposits, as the joint modelling of the related attributes using the traditional co-simulation approaches is computationally intensive and may be impractical for use in the industrial environment. This paper presents the construction of risk-integrating grade-tonnage curves for a complex copper deposit in northern Brazil, by jointly simulating its key geochemical attributes of interest: Cu, Fe and K. The joint conditional simulation of these elements is based on Minimum/Maximum Autocorrelation Factors (MAF). MAF is an approach, based on principal components, that spatially decorrelates the variables involved to non-correlated factors. MAF’sspatial decorrelation at any lag distance is the main and critical difference of this approach from the principal component approach attempted in the past. In the MAF approach, the independent factors are individually simulated and back-transformed to the conditional simulations of the correlated deposit attributes that reproduce the cross-correlations of the original variables. Keywords: Joint simulation; mini/max autocorrelation factors; grade-tonnage curves.