Gis based aproach to optimization of exploration drilling for lirhanda gold exploration project, western Kenya.

In an effort to realize commercial gold mining in Western Kenya, its exploration has been done over the years and recently in 2015, a gold resource worth 1.31 Million ounces of gold worth 1.65 billion US Dollars was announced by Acacia Exploration Company in the Lirhanda Corridor of Western part of Kenya. In addition, Acacia gold Ltd reported mineralised zones on the neighbouring prospects, approximately one kilometre away from the Acacia prospect, but stated that at that stage the material remained unclassified due to drill density and the need to further understand the controls on the mineralisation and its continuity. Further exploration and research has been proposed to move this existing target mineralisation into the “Inferred Resource” category and to expand the scale of the targeted mineralisation by exploring areas of the neighbouring prospects, which are large gold in-soil anomalies with positive initial drill results. According to results provided by Acacia Exploration Kenya from their drilling program, the main zones of gold mineralisation at Acacia prospect are hosted by sheared pillow and sheared massive basalts of the mafic volcanic unit. They are associated with quartz, quartz-carbonate and quartz-vanadium mica veinlets and sulphide mineralisation is present in the form of pyrite, pyrrhotite, sphalerite, arsenopyrite, and molybdenite Sometimes minor graphite and native gold are also recorded within the zones. The Acacia and Bushiangala prospects mineralisation style is classified as orogenic, shear-zone-hosted quartz-carbonate vein subtype, as defined by Robert et al. 2007. In this study, an attempt has been made to derive a GIS model from preliminary exploration data for identifying targets which will be consistent to Acacia findings and use such to reduce exploration expenditure in the future exploration programs in the area. This study, employing interpolation and data integration techniques provided by the GIS software, utilised preliminary exploration data obtained from geophysical, remote sensing and soil geochemical surveys together with the available supporting geology to identify more prospective areas during gold exploration. After Validation the more prospective locations for drilling were found to be those within mudstones, conglomerates and andesite lithologies as well as along the interpreted magnetic targets and fault lines and are therefore hereby referred to as the optimum signatures for gold mineralization in Lirhanda corridor. The possible geochemical signatures are Fe-Nb-As-Mo-Cu-Zn-Au, Fe-Cu-Zn-Au, Fe-As-Cu-Zn-Au. These indications lead to what Acacia had previously established and hence such a model is important to define drilling targets with more certainty. This optimization technique may be applied for exploration optimisation in other goldfields in Kenya and other countries, which occur in similar geological settings.