Modelling Combined Geological and Grade Uncertainty of a Gold Deposit Using MPS and SGS

Traditionally within the mining industry, single models for both grade and geology of orebodies are created upon which all mine development decisions are based. These models provide a single interpretation of the extent and continuity of the mineralization envelope based on solids and sections interpreted from relatively wide spaced drilling i.e. the models infer behaviour of grade and geology at smaller/local scales based on data available at wider scales. The variable behaviour of grade and geology cannot be derived from single kriged resource models. In recognition of this, Newmont Mining Corporation typically uses Sequential Gaussian Simulation (SGS) to quantify grade variability and to determine its effect on some of these mine development decisions. In most of these studies the mineralized envelope remains fixed and grade simulations are generated within a fixed volume. To account for uncertainty in the geology/ mineralization envelope Newmont Mining Corporation has been experimenting with Multiple Point Statistics (MPS). Multiple-Point Statistics is an emerging technique, which can be used to generate multiple, geologically realistic, realizations of data that displays complex non-linear features. MPS uses a conceptual model of the geology, called a Training Image (TI), to infer these high-order spatial relationships. The multiple realizations allow for an assessment of the geologic uncertainty, which can be further combined with grade simulations to generate a more complete picture of the true uncertainty of a mineral deposit.