Direct Block-Support Simulation of Grades in Multi-Element Deposits: Application to Recoverable Mineral Resource Estimation at Sungun Porphyry Copper-Molybdenum Deposit

"Recoverable mineral resources assessment has become a standard geostatistical application in the mining industry, with various geostatistical techniques currently available. This investigation aimed to improve the prediction at the Sungun deposit and to obtain mineral resource models capable of handling (i) the change of support from drill-hole composites to selective mining units (SMUs), (ii) the multivariate nature of the ore control selection criteria that involves both copper and molybdenum grades; and (iii) the local uncertainty on the true (unknown) grades. The solution presented in this paper is to use direct block-support sequential cosimulation in order to construct a set of alternative outcomes of the copper and molybdenum grades on block support over the deposit, with no need for storing point-support values, hence with a considerable gain in memory management and CPU time. The grade realizations so obtained are then processed to calculate the uncertainty in the mineral resources that can be recovered above given cut-off grades, both globally and on a blockby- block basis. IntroductionGeostatistical methods are widely used by 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)."