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Exploring mineral domains with genetic algorithm

In this paper we present a novel application of genetic algorithm for obtaining mineral domains. An important step in mineral exploration is to identify potential underground areas for mining purposes. Cylindrical cores of rock are extracted from the subsurface using diamond drilling and data is logged on the cores leading to geo-data sets. These geo-datasets are analysed to obtain domains i.e. regions of unique characteristics. We have developed a genetic algorithm based approach to identify mineral domains from geo-data sets. A special feature of the proposed approach is that it can separate the domains by preserving their spatial continuity that conventional point-based and window-based clustering fail to capture. We have evaluated the proposed method on gold-assay and geochemical datasets obtained from a gold mine in Western Australia. Experimental results demonstrate that the proposed method can identify domains accurately and also outperform point-based and window-based clustering.