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mining companies to determine a resource model of the tonnage and head grade of a potential orebody, which is one of the first and most critical inputs underpinning any mining project. The prediction of the grade, tonnage, and recoverable metal for a particular mining plan and the corresponding financial forecast constitute the main technical risks in mineral resource evaluation. The conventional approach to this problem is to predict the mineral grade for constant volumes relevant to the mining plan and to base the recoverable mineral resource calculations on those predictions. Alternatively, one can directly predict the local variability in the mining block grades based on a spatial distribution model (David 1988; Rossi and Deutsch 2014). Multiple realizations can also be constructed by conditional simulation, providing a more complete representation of block grade uncertainty, as well as the uncertainty over multiple blocks. Simulation methods allow quantification of the uncertainty of the mineral resource prediction risks in downstream studies such as mine design, mine planning, or operational optimization studies; the risk assessment is achieved after applying transfer functions to the conditional simulation models (Dimitrakopoulos 2012; Rossi and Deutsch 2014). Recoverable mineral resource prediction and simulation models should be capable of handling: (1) a change of volumetric support, which is a common and critical issue in modelling regionalized variables such as mineral grades as, invariably, the volumetric support of the available data (e.g., drill-hole composites) is much smaller than the blocks on which the model is based (Emery and Ortiz, 2011); (2) the multivariate nature of the ore control selection criteria (Montoya et al., 2012); (3) the local uncertainty, which refers to the probability distributions of the actual values at specific locations (Khan and Deutsch 2015). The solution is therefore to construct a multivariate block-support simulation and a post-processing aimed at producing a multivariate recoverable mineral resource evaluation. The usual approach used for simulating grade values onto a block support consists in performing point-support simulation on a dense grid that covers the region of interest, and then averaging within relevant selective mining units (SMUs) or blocks in order to develop a simulated block-support (Boucher and Dimitrakopoulos, 2009; Emery, 2009; Emery and Ortiz, 2011). This procedure has two computational disadvantages: it is timeconsuming and requires a significant amount of computer memory. An alternative is direct block-support simulation, which avoids simulating onto a grid that discretizes the blocks. This idea, as originally proposed by Journel and Huijbregts (1978), is based on separate simulation and conditioning steps. Boucher and Dimitrakopoulos (2009) Direct block-support simulation of grades in multi-element deposits: application to recoverable mineral resource estimation at Sungun porphyry copper-molybdenum deposit

journal of the southern african institute of mining and metallurgy/journal of the south african institute of mining and metallurgy

Direct block-support simulation of grades in multi-element deposits: application to recoverable mineral resource estimation at Sungun porphyry copper-molybdenum deposit