Recognition of an enhanced multi-element geochemical signature of porphyry copper deposits for vectoring into mineralized zones and delimiting exploration targets in Jiroft area,SE Iran |
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| Institution: | 1. State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan 430074, China;2. Department of Earth and Oceans, James Cook University, Townsville, Queensland 4811, Australia;1. Department of Earth and Environmental Sciences, University of Windsor, 401 Sunset Ave., Windsor, Ontario N9B 3P4, Canada;2. Department of Earth Sciences, Western University, 1151 Richmond St., London, Ontario N6A 3K7, Canada;3. Geological Survey of Canada, 601 Booth St., Ottawa, Ontario K1A 0E8, Canada;1. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang 830011, China;2. Xinjiang Research Centre for Mineral Resources, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang 830011, China;3. Xinjiang Key Laboratory of Mineral Resources and Digital Geology, Urumqi, Xinjiang 830011, China;4. Cooperative Innovation Center for Scarce Mineral Resources Exploration, China University of Geosciences (Wuhan), Wuhan, Hubei 430074, China;5. Faculty of Earth Resources, China University of Geosciences, Wuhan 430074, China;6. Geological Sciences, School of Agriculture, Engineering and Sciences, University of KwaZulu-Natal, Westville, South Africa;1. Department of Mining Engineering, Faculty of Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran;2. Camborne School of Mines, University of Exeter, Penryn, UK;3. Young Researchers and Elite Club, South Tehran Branch, Islamic Azad University, Tehran, Iran;4. Department of Economic Geology, Tarbiat Modares University, Tehran, Iran |
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| Abstract: | Delimiting exploration targets using geochemical exploration data can be a challenging issue when different geochemical signatures represent the same deposit-type sought. In this regard, fuzzy operators have been used to integrate different geochemical evidence layers into a single model for generating target areas. In this paper, a GIS-based expected value function was adapted to integrate different geochemical evidence layers into a stronger geochemical signature for delimiting exploration targets. Then, the expected value function and fuzzy operators were compared. The comparison demonstrated that the former is more efficient than the later for generating a stronger geochemical evidence layer. The higher efficiency of the expected value function is because it simultaneously uses the value of all input variables and their relative importance in the process of integration. The proposed approach was evaluated by using a lithogeochemical data set for prospecting porphyry-Cu deposits in Jiroft area, Kerman province, southeast of Iran, as a case study. |
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| Keywords: | Expected value Fuzzy operators GIS-based integration Enhanced geochemical evidence layer Delimiting target areas Lithogeochemical data |
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