A Comparative Study Between Ordinary Kriging (OK) and Sequential Gaussian Simulation (SGS) in Determination of Underground Mining Limit

The underground mining limit, which defines the shape of stopes and mine layout, is important for determining economic value and net present value (NPV). Creation of a precise grade model using geostatistical estimation for ore deposit in one of the first attempts during underground mine planning and designing. In the process of grade estimation entire a block model, underestimation can result in loss of economic value, whereas overestimation may unnecessarily increase that. To resolve these kind of problems, conditional simulation with considering uncertainty during orebody grade modeling as a reliable approach and most widely used, can be useful and increase the accuracy of a mining project design. The aim of this study is to compare kriging method and sequential gaussian conditional simulation (SGS) in determining the optimum underground stope layout using a new heuristic algorithm. For this purpose, a set of simulated realizations generated in S-GeMS software and named average simulated block model. Then the results of Stope numbers, average grade and economic value compared with kriging block model and studied carefully. Results obtained by the study indicate that conditional simulation is more acceptable than kriging method so that economic value of project was significantly increased.