Multiple-point geostatistical simulation for mine evaluation with aeromagnetic data. Issue 6 (1st November 2018) - Hong, Jinpyo; Oh, Seokhoon; Cho, Seong-Jun
Abstract : Multiple-point geostatistical simulation (MPS) was applied to develop 3D ore models matched to surrounding geological information accompanying aeromagnetic data using a training image (TI). Conventional 3D geological models generated from a limited number of boreholes and other geological information may be useful for evaluating the mineral resources around the boreholes, while also bearing uncertainty regarding the evaluation of the ore body over the entire area. Geostatistical analysis accompanying the geophysical interpretation is adopted to reduce the uncertainty of the 3D ore model. Among the geostatistical methods, MPS based on a TI made from available geological information is chosen to simulate the configuration and distribution of the ore body according to the geological structure. The present study proposes a method for reducing the uncertainty of the 3D ore model, applying MPS for mine evaluation to create probabilistic ore models and analysing the correlation between the models and geophysical data. This method was applied to a metal mine located in Korea. Single normal equation simulation (SNESIM) was chosen as the simulation algorithm, and aeromagnetic data were used to support the analysis of simulated models. With comparison/analysis of the probabilistic ore model and geophysical data, the 3D geological model utilising MPS represented the configuration and distribution of the ore body well according to the geological structure. The SNESIM cluster results indicated high reliability for the final interpretation of the 3D models. Abstract : Multiple-point geostatistical simulation (MPS) was applied to develop 3D ore models matched to surrounding geological information accompanying aeromagnetic data using training image. The present study proposes a method for reducing the uncertainty of the 3D ore model, applying MPS to create probabilistic ore models and analysing the correlation between the models and geophysical data.