Prospectivity mapping for high sulfidation epithermal porphyry deposits using an integrated compositional and topographic remote sensing dataset

Ferrier, Graham; Ganas, Athanassios; Pope, Richard

Abstract

© 2019 Elsevier B.V. The targeting and discovery of epithermal porphyry mineral deposits can be enhanced using a structured quantitative methodology to analyse the distribution of ore deposits and model their spatial association with exploration evidence providing improved understanding on the controls of ore deposition. A novel exploration tool integrating field and ASTER SWIR and TIR satellite imagery has been developed which provides an enhanced means of resolving surface expressions of the residual silica core of the lithocap. The alteration zones were clearly resolved by the remote sensing data and an intimate spatial relationship between high-grade altered rocks and topographic highs was identified at a number of locations. A Mineral Prospectivity Modelling (MPM) approach, parameterized by the results of the remote sensing study, using a GIS-based weighted linear combination implementation of a Multi-Criteria Evaluation approach and utilising a fuzzy Analytical Hierarchy Process to elucidate expert knowledge has been implemented to target high sulfidation epithermal porphyry deposits on the Island of Lesvos, Greece. The results from this integrated altitudinal-compositional modelling approach closely matched the hydrothermal alteration mapped in the field supporting the accuracy of this MPM approach.

Citation

Ferrier, G., Ganas, A., & Pope, R. (2019). Prospectivity mapping for high sulfidation epithermal porphyry deposits using an integrated compositional and topographic remote sensing dataset. Ore Geology Reviews, 107, 353-363. https://doi.org/10.1016/j.oregeorev.2019.02.029

• Journal Article Type: Article
• Acceptance Date: Feb 25, 2019
• Online Publication Date: Feb 26, 2019
• Publication Date: Apr 1, 2019
• Deposit Date: Apr 14, 2019
• Publicly Available Date: Apr 15, 2019
• Journal: Ore Geology Reviews
• Print ISSN: 0169-1368
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 107
• Pages: 353-363
• DOI: https://doi.org/10.1016/j.oregeorev.2019.02.029
• Public URL: https://hull-repository.worktribe.com/output/1597781
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0169136818307522?via%3Dihub
• Contract Date: Apr 15, 2019