Mineralisation potential assessment using analytical hierarchy process (AHP) modeling technique: A case study of Ilesha schist belt, southwestern Nigeria

A mineralisation potential assessment in part of Ilesha Schist belt of southwestern Nigeria was carried out using multi criteria decision analysis (MCDA) in the context of analytical hierarchy process (AHP). Three parameters sourced from aeromagnetic, electrical resistivity and geological data were identified to favour gold mineralisation in the study area. These parameters include lineament density (Ld), lithology (Lt), and electrically derived coefficient of anisotropy (An). The application of data enhancement techniques such as total horizontal derivative, 3-D Euler deconvolution and source edge detection were employed in the production of lineament map of the study area. Two hundred and sixty-five (265) vertical electrical sounding (VES) points were investigated using Schlumberger configuration. Coefficient of anisotropy derived from the Dar-Zarouk parameters was obtained from the synthesized VES data. The lithologic information was obtained from the existing geological map of the area. The orientations of lineaments displayed on the aeromagnetic results suggest predominantly NE-SW trending structures, which are characteristic of the Pan African orogenic events in the area. However, few of the E-W trending lineaments are imprints of secondary structural alteration. Furthermore, the Euler deconvolution solutions revealed that the area is characterised by geological contacts with estimated depth of 94–600 m. The coefficient of anisotropy results obtained from the geo-electric parameters vary from 1.00–2.87. AHP weighting and ranking technique was used to develop a reliable mineralisation potential model (MPM). In line with the recommended lower limit of 10 %, the consistency ratio of the developed model is 9.61 %. The produced MPM was classified into low, moderate and high mineralisation potential zones. Preliminary validation of the MPM using the existing pits in the area showed 79 % success rate. The validation of the model using the existing geochemical information from the previous studies indicated 85 % agreement with the conceptual model; thus, confirming the reliability of the produced MPM. The developed model is therefore believed to serve as a future reference in the resource management of the study area.