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Data Mining of a Geoscience Database Containing Key Features of Gold Deposits and Occurrences in Southwestern Uganda: A Pilot Study

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Abstract

Data mining is a promising new tool in mineral exploration. Here, we combined data-mining procedures with spatial prediction modeling for gold exploration targeting in the Buhweju area in southwestern Uganda. It was employed in a data-rich context of unavoidably partly redundant and correlated information that offered challenges in extracting significant relationships. Our study utilized a database of co-registered digital maps related to gold mineralization. It comprised Landsat TM, Shuttle Radar Topographic Mission (SRTM), and geophysical (radiometric and magnetic) datasets for geological and structural mapping. The locations of 15 orogenic gold deposits and 87 gold occurrences were obtained from the Geological Survey of Uganda database. These were considered direct evidence of the presence of gold mineralization. The geological and geophysical settings at the gold deposit/occurrences locations were based on geological units as host rocks, contacts, and structural elements, together with continuous field values of geophysics, radiometry, and other remotely sensed imagery. A gold exploration targeting proposition (Tp) was defined as: “That a point p within the study area contains a gold deposit given the presence of spatial evidence.” All outstanding combinations of spatial evidence were obtained using empirical likelihood ratios. With a data-mining strategy, the ratios were filtered and modeled to identify stronger spatial associations, to rank the study area according to the likelihood of future discoveries, to represent ranking quality, to estimate associated uncertainty, and to select prospective target areas. The empirical likelihood ratios facilitated a transparent strategy for generating prediction patterns and extracting small prospective target areas with higher likelihood of discovery and lower-ranking uncertainty. Conclusions are provided on the knowledge extraction for prospectivity with further data and the challenges of reducing the arbitrariness of decisional steps.

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Acknowledgments

Between 2008 and 2012, Uganda was remapped by the Geological Survey of Finland, GTK, in a consortium as part of the World Bank-funded Sustainable Management of Mineral Resources Project SMMRP on “Geological mapping, geochemical surveys, and mineral resources assessment in selected areas of Uganda." The consortium led by GTK involved the collaboration of the Entebbe Department of Geological Survey and Mines, DGSM in Uganda, and the International Institute for Geoinformation Sciences and Earth Observation, ITC, in The Netherlands. Various MSc study projects were conducted under this collaboration. This research is a product and continuation of it. Our warm appreciation goes to all the researchers who, in one way or other, allowed us to use some of their manuscripts and datasets that gave us the ideas presented in this paper. Most, if not all, have been cited in this paper. We are grateful for the support and cooperation of Mr. Tapio Lehto of GTK, who allowed us to use the geological field geo-datasets collected for the Mapping Project. We thank Mr. John Odida, the former Director of the Ugandan Geological Survey, for granting access to the fieldwork sites. We also are grateful to three reviewers for their constructive comments, which helped us improve the readability of our paper: Jeff R. Harris (Harris Geoscience, Canada), Greg A. Partington (Kenex Ltd., New Zealand), and Oliver P. Kreuzer (James Cook University, Australia).

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  1. Tsehaie Woldai

    Present address: School of Geosciences, University of Witwatersrand, Johannesburg, South Africa

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  1. DISAT, University of Milano-Bicocca, Milan, Italy

    Andrea G. Fabbri

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Correspondence to Tsehaie Woldai.

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Woldai, T., Fabbri, A.G. Data Mining of a Geoscience Database Containing Key Features of Gold Deposits and Occurrences in Southwestern Uganda: A Pilot Study. Nat Resour Res 31, 2289–2319 (2022). https://doi.org/10.1007/s11053-022-10073-4

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