Mining Geostatistics and Operations Research in Mine Planning
Mining is one of the disciplines in which geostatistics and operations research are frequently used to solve various engineering problems. As mining is a capital intensive industry, the companies always tend to minimise the costs to ensure the overall projects are feasible. For instance, at prospecting and exploration stage where the boreholes are rather sparsely spaced, geostatistics provides a critical tool to assign grades to unknown locations and construct accurate 3D models representing the ore body. The uncertainty associated with the grade variability and ore body thickness, which may directly have an impact on the viability of the project, can also be accounted for non-linear geostatistical algorithms and stochastic simulation approach. Given the exploitation stage of the mining project, there are also various mine planning-related problems that need to be tackled to ensure the economic viability of the project. Some of the mine planning problems include mine design, determination of the optimum cut-off grade policy, long- and short-term production scheduling and equipment selection and dispatching. Operations research is used to provide optimum solutions to the aforementioned problems. There are however still various challenges in relation to ore body modelling and mine planning activities depending on the mineral commodity that is mined. The aim of this session is therefore to show several examples where the geostatistical and operation research algorithms are implemented in mining data sets. The session also welcomes the contributions focusing on new theory/algorithms and practical applications.
Christien Thiart, Oktay Erten and Erkan Topal