Reducing subjectivity in multi-commodity mineral prospectivity analyses: Modelling the west Kimberley,Australia |
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| Institution: | 1. Centre for Exploration Targeting, The University of Western Australia, 35 Stirling Hwy, Crawley, WA 6009, Australia;2. Economic Geology Research Centre, James Cook University, Townsville, Queensland 4814 Australia;3. Geological Survey of Western Australia, 100 Plain Street, East Perth, WA 6004, Australia;4. Geology Department, Ministry of Mineral Resources, Imaneq 1A 201, 3900 Nuuk, Greenland;1. State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Beijing 100083, China;2. Open Laboratory of Orogenic and Crustal Evolution, Peking University, Beijing 100871, China;3. Henan Provincial Non-ferrous Metals Geological and Mineral Resources Bureau, Zhengzhou 450016, China;1. School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China;2. Institute of Land Resources and High Techniques, China University of Geosciences, Beijing 100083, China;3. The Beijing Key Laboratory of Development and Research for Land Resources Information, China University of Geosciences, Beijing 100083, China;4. School of Geophysics and Information Technology, China University of Geosciences, Beijing 100083, China;1. Geoscience Australia, Canberra, ACT 2601, Australia;2. Research School of Earth Sciences, Australian National University, Canberra 2601, Australia;3. Geological Survey of Queensland, Brisbane, Australia;1. Geological Survey of Queensland, PO Box 15216, City East, QLD 4002, Australia;2. Centre for Exploration Targeting, School of Earth and Environment, The University of Western Australia, Crawley, WA 6009, Australia;3. Department of Geological Sciences, Stockholm University, Stockholm 10691, Sweden |
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| Abstract: | Predicting realistic targets in underexplored regions proves a challenge for mineral explorers. Knowledge-driven prospectivity techniques assist in target prediction, and can significantly reduce the geographic search space to a few locations. The mineral prospectivity of the underexplored west Kimberley region was investigated following interpretation of regional gravity and magnetic data. Emphasis was placed on identifying geological structures that may have importance for the mineral prospectivity of the region. Subsurface structure was constrained through combined gravity and magnetic modelling along three transects. Crustal-scale structures were interpreted and investigated to determine their depth extent. These interpretations and models were linked to tectonic events and mineralization episodes in order to map the distribution of minerally prospective regions using a knowledge-driven mineral systems approach. A suite of evidence layers was created to represent geological components that led to mineralization, and then applied to each mineral system where appropriate. This approach was taken to provide a more objective basis for prospectivity modelling. The mineral systems considered were 1) magmatic Ni-sulphide, 2) carbonate-hosted base metals, 3) orogenic Au, 4) stratiform-hosted base metals and 5) intrusion-related base metals (including Sn–W, Fe-oxide–Cu–Au and Cu–Au porphyry deposits). These analyses suggest that a geologically complex belt in the Kimberley Basin at the boundary to the King Leopold Orogen is prospective for magmatic-related hydrothermal mineral systems (including Ni, Au and Cu). The Lennard Shelf is prospective for carbonate-hosted base metals around a feature known as the 67-mile high, and parts of the King Leopold Orogen are prospective for stratiform-hosted base metals. These results show that knowledge-driven mineral system modelling is effective in identifying prospectivity in regional-scale studies of underexplored areas, as well as drastically reducing the search space for explorers working in the west Kimberley. |
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