Conventional open pit mine design methods ignore geological uncertainty in terms of metal content and material types which can impact the quantities processed in multiple process mining operations. A stochastic framework permits the use of geological simulations to quantify geological uncertainty; however, existing models have either not been extended to pushback design for mines with multiple elements, multiple materials and multiple destinations, or are limited in their ability to incorporate joint local uncertainty represented through sets of geological simulations. This work aims to integrate grade and material uncertainty in pushback design for open pit mines. Two formulations are proposed to modify existing pushback designs to reduce risk in terms of the amounts of material going to each destination, while maintaining similar pushback sizes when compared to the original design. The proposed formulations are applied at BHP Billiton's Escondida Norte mine, Chile, and show a 35–61% reduction in variability in terms of quantities of material sent to the various processes.

Traditional geostatistical modelling of orebodies and estimation of grade–tonnage curves do not account for the uncertainty of the orebody grades and tonnages. Geological interpretations of complex shapes are often over-constrained, and therefore do not properly identify the location of the ore. In these situations, tonnage is often under-estimated and grade is over-estimated, resulting in orebody models used for mine planning that lead to costly financial decisions. This paper presents an approach aiming to better assess the uncertainty in an orebody model. The approach is applied to Vale's West Orebody of the Coleman McCreedy Mine, a poly-metallic deposit containing nickel, copper, gold, platinum and palladium. To encapsulate the orebody's variability and uncertainty, the nickel–copper sulphide mineralized zone is simulated using the single normal equation simulation method. The realizations serve as the orebody models from which the grades of multiple elements are jointly simulated using Min/Max Autocorrelation Factors. The final result is a series of equiprobable representations of the mineralization that incorporates both grade and tonnage uncertainty. The case study indicates that had conventional orebody estimations been used, there would have been a 10% over-estimation of orebody volume, along with significant over-estimation of low-grade material and under-estimation of high-grade material.