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A Comparative Analysis of Weights of Evidence, Evidential Belief Functions, and Fuzzy Logic for Mineral Potential Mapping Using Incomplete Data at the Scale of Investigation

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Abstract

Large amounts of digital data must be analyzed and integrated to generate mineral potential maps, which can be used for exploration targeting. The quality of the mineral potential maps is dependent on the quality of the data used as inputs, with higher quality inputs producing higher quality outputs. In mineral exploration, particularly in regions with little to no exploration history, datasets are often incomplete at the scale of investigation with data missing due to incomplete mapping or the unavailability of data over certain areas. It is not always clear that datasets are incomplete, and this study examines how mineral potential mapping results may differ in this context. Different methods of mineral potential mapping provide different ways of dealing with analyzing and integrating incomplete data. This study examines the weights of evidence (WofE), evidential belief function and fuzzy logic methods of mineral potential mapping using incomplete data from the Carajás mineral province, Brazil to target for orogenic gold mineralization. Results demonstrate that WofE is the best one able to predict the location of known mineralization within the study area when either complete or unacknowledged incomplete data are used. It is suggested that this is due to the use of Bayes’ rule, which can account for “missing data.” The results indicate the effectiveness of WofE for mineral potential mapping with incomplete data.

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Acknowledgements

The author wishes to acknowledge the assistance from the Troy Resources for their ongoing support in terms of funding the project and providing the data for the Carajás mineral province. Craig Hart, Orestes Santos, Cam McCuaig, Steffen Hagemann, David Otterman, and Ezequiel Silva are also thanked for ongoing conversations on orogenic gold mineralization.

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Authors and Affiliations

  1. Centre for Exploration Targeting, University of Western Australia, Crawley, WA, 6009, Australia

    Arianne Ford & John M. Miller

  2. Troy Resources Limited, Unit 12, First Floor, 11 Ventnor Ave, West Perth, WA, 6005, Australia

    Augusto G. Mol

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  1. Arianne Ford
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Correspondence to Arianne Ford.

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Ford, A., Miller, J.M. & Mol, A.G. A Comparative Analysis of Weights of Evidence, Evidential Belief Functions, and Fuzzy Logic for Mineral Potential Mapping Using Incomplete Data at the Scale of Investigation. Nat Resour Res 25, 19–33 (2016). https://doi.org/10.1007/s11053-015-9263-2

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  • DOI: https://doi.org/10.1007/s11053-015-9263-2

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