Mapping of hydrothermal alterations related to gold mineralization within parts of the Malumfashi Schist Belt, North-Western Nigeria

Abstract

Remote sensing methods are a vital alternative for regional exploration surveys. Many ore deposits (e.g., epithermal, porphyry-related, volcanogenic massive sulphides, etc.) have distinct distribution patterns of alteration zones that can be used for recognizing this mineralization. Several known goldfields are distributed within the basement rocks of western Nigeria. The area of interest, Malumfashi Schist Belt, is located in North-Western Nigeria and is characterized by gneisses and metasediments that were intruded by Pan-African granitoids. Gold mineralization occurs as veins and veinlets that are associated with hydrothermal alteration zones (i.e., argillic, phyllic, and propylitic). Hence, the discrimination of these alteration zones is one of the key indicators for new prospective zones of gold mineralization in this metallogenic belt. In the present study, Landsat Enhanced Thematic Mapper+ (Landsat-7 ETM+) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data were processed and integrated with the aim to identify possible locations for gold mineralization within the Malumfashi Schist Belt. For this purpose, the band ratio techniques and Principal Component Analysis (PCA) were applied to identify, enhance and map the different alteration types, while fractal analysis was utilized to quantify the degree of alteration within each processed image. Using the multi-criteria evaluation method, the discretized images obtained from the fractal analysis were weighted and integrated into an enhanced possible location for gold occurrences. A receiver operating curve/Area under curve analysis was then used to evaluate the reliability of the predictive model. Both spatial and GIS analyses indicate that gold mineralization displays a proximal relationship to hydrothermal alteration data. We can map sets of alteration minerals which mainly represent new and good ore prospects for the investigated area. A sensitivity analysis points out a predictive accuracy of 78%, which suggests the model is capable of predicting gold occurrences within the study region. Besides, the results showed that the prospective zones of gold accumulations mainly occur within metasedimentary units. It is recommended that the studied dataset provide a potential tool for mapping alteration minerals related to gold deposits that can be applied in other regions with analogous geological setting.