Logistic-Based Translation of Orogenic Gold Forming Processes into Mappable Exploration Criteria for Fuzzy Logic Mineral Exploration Targeting in the Kushaka Schist Belt,North-Central Nigeria

This paper applied a logistic-based fuzzy logic inference system to integrate critical factors that could control orogenic gold mineralization in part of the Kushaka schist belt, north-central Nigeria to develop a process-based mineral potential mapping (MPM) of the area. The critical factors from geophysical and geological dataset were weighted using logistic functions. The fuzzy logic inference system provides the capability to handle complex geological processes that culminated in orogenic gold mineralization as well as minimizing systemic uncertainties/fuzziness that often plague MPM. The results of this work show that granitic intrusions with fuzzy scores of 0.67–0.90 played a major role in generating high geothermal gradient in the area. Seventy percent of the existing gold mine sites in the area spatially coincide with metasedimentary rocks, having fuzzy scores of 0.7–0.9; this suggests metasedimentary rocks as being responsible for the production of gold fluid and ligands in the area. The evidence of hydrothermal activity, with fuzzy scores of 0.53 and 0.91, confirms the occurrence of mineralization associated with quartz veins and granite rocks. Lithological contacts and faults, having fuzzy scores of 0.60–0.80, presumably contribute to the localization of orogenic gold mineralization in the area. Emerging from the results, favorable zones for primary orogenic gold mineralization in the area occurred predominantly on granite gneiss and quartz veins. The mineral potential map was found consistent with the local geology, structural styles and hydrothermal alteration signatures in the area, and its validation using the existing locations of geochemical anomalies and prediction–area rate curve in the study area showed 75 and 72% agreement, respectively, thus confirming the reliability of the developed mineral potential map for resource management.