Predictive mapping of prospectivity for orogenic gold in Uganda

Abstract

Integration of enhanced regional geo-datasets has facilitated new geological interpretation and modelling of prospectivity for orogenic gold in southwestern Uganda. The geo-datasets include historical geological maps, geological field data, digital terrain models, Landsat TM data and airborne geophysical data. The study area, bordered by the western branch of the East African Rift, covers a range of different aged terranes including the Archaean basement gneisses, Palaeoproterozoic volcano-sedimentary Buganda Toro Belt, Mesoproterozoic clastic sedimentary Karagwe Ankolean Belt and several outliers of undeformed Neoproterozoic sediments.The mineral systems approach to practical exploration targeting requires a framework to link conceptual models of mineralisation with available data. A conceptual model requires good understanding of key processes and their timing within the geodynamic history of an area. The challenge is that processes cannot be mapped, only their results or effects. In this study, a district-scale (1:100,000) investigation is considered appropriate given the scarcity of geological information and the absence of world-renowned gold deposits in southwestern Uganda. At this scale of orogenic gold mineral systems understanding, evidence for the source of gold, active pathways and the physical traps are considered critical. Following the mineral system approach, these processes critical to orogenic gold systems are translated into district-scale mappable proxies using available regional-scale datasets. Tectono-stratigraphic domains, mantle indicators and gold occurrences represent the “source of gold” as a critical process. Zones of hydrothermal alteration were extracted from radiometric data, structures involved in the orogenies and terrane contacts were extracted to represent the active pathway as a critical process and finally the physical throttle is represented by rheological contrasts and geological complexity. Then, the knowledge-driven multi-class index overlay method was used to integrate predictor layers representing those processes in order to model orogenic gold prospectivity into a single map. Weighting of the predictor layers, prior to integration, occurs at the level of the critical process and takes into account the relative importance of the critical process mineralisation, the representativeness of a proxy and the accuracy of the proxy. The resultant prospectivity model shows that 83% of all gold occurrences are delineated within predicted prospective areas covering 30% of the study area. Eight sub-areas, covering 2500km2, have been recommended for follow-up exploration.