A prediction model for important mineral resources in China |
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| Institution: | 1. MLR Key Laboratory of Metallogeny and Mineral Assessment, Institute of Mineral Resources, Chinese Academy of Geological Sciences, Beijing 100037, China;2. China University of Geosciences (Beijing), Beijing 100083, China;1. MLR Key Laboratory of Metallogeny and Mineral Assessment, Institute of Mineral Resources, Chinese Academy of Geological Sciences, Beijing 100037, China;2. State Key Laboratory of Isotope Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Wushan, Guangzhou 510460, China;1. School of Geosciences and Info-Physics, Central South University, Changsha 410083, China;2. Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, Changsha 410083, China;3. Beijing Institute of Geology for Mineral Resources, Beijing 100012, China;4. Centre for Exploration Targeting, ARC Centre of Excellence for Core to Crust Fluid Systems, The University of Western Australia, Crawley, WA 6009, Australia;5. MLR Key Laboratory of Metallogeny and Mineral Assessment, Institute of Mineral Resources, CAGS, Beijing 100037, China;1. State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Beijing 100083, China;2. Minmetals Exploration & Development Co., Ltd., Beijing 100010, China;3. Transforming the Mining Value Chain, ARC Industrial Transformation Research Hub, CODES, ARC Centre of Excellence, University of Tasmania, GPO Box 79, Hobart, Tasmania 7001, Australia;1. Key Laboratory of Mineral Resources, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China;2. University of Chinese Academy of Sciences, Beijing 100049, China;3. Key Laboratory of Metallogeny and Mineral Assessment, Institute of Mineral Resources, Chinese Academy of Geological Sciences, Beijing 100037, China;4. School of Earth Sciences and Resources, China University of Geosciences (Beijing), Beijing 100083, China;5. Research Institute No. 290, China National Nuclear Corporation, Shaoguan 512026, China;6. Geological Publishing House, Beijing 100083, China;1. Institute of Mathematical Geology and Remote Sensing Geology, Faculty of Earth Resources, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China;2. Hubei Institute of Land Surveying and Mapping, 199 Aomen Road, Wuhan 430010, China |
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| Abstract: | Prediction models for mineral resources provide an analytical foundation and method to express the results of resource evaluations. The project “China National Mineral Resources Assessment Initiative” was conducted during 2006–2013, with the aim to determine the location, quantity, and quality of 25 important mineral resources occurring at depths of <1 km. There are currently 80 integrated prediction models on the scale of III–level metallogenic belts in use across China. The Huangshaping Pb–Zn polymetallic deposit, Hunan province, China, is used as a case study to establish methods and processes for developing a mineral resource prediction model that would be used for exploration targeting. The construction of prediction models requires the development of a classification scheme for the proposed prediction method appropriate for the prediction area. An initial metallogenic model is quantitatively transformed to a prospecting model, and then a prediction model. The incorporation of additional methodology, analysis of a comprehensive geological database, and correlation of asymmetric information between the well–explored typical deposit area and regional prediction area, yield an integrated prediction model. This paper also discusses the prediction modeling theory, and presents 12 models used for mineral assessments. |
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| Keywords: | Mineral Resources Assessment Prediction method Metallogenic model Prospecting model Integrated prediction model |
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