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3D Mineral Prospectivity Mapping Based on Deep Metallogenic Prediction Theory: A Case Study of the Lala Copper Mine, Sichuan, China

  • Special Issue on Digital Geosciences and Quantitative Exploration of Mineral Resources
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Abstract

With the decrease in surface and shallow ore deposits, mineral exploration has focused on deeply buried ore bodies, and large-scale metallogenic prediction presents new opportunities and challenges. This paper adopts the predictive thinking method in this era of big data combined with specific research on the special exploration and exploitation of deep-earth resources. Four basic theoretical models of large-scale deep mineralization prediction and evaluation are explored: mineral prediction geological model theory, multidisciplinary information correlation theory, mineral regional trend analysis theory, and mineral prediction geological differentiation theory. The main workflow of large-scale deep resource prediction in the digital and information age is summarized, including construction of ore prospecting models of metallogenic systems, multiscale 3D geological modeling, and 3D quantitative prediction of deep resources. Taking the Lala copper mine in Sichuan Province as an example, this paper carries out deep 3D quantitative prediction of mineral resources and makes a positive contribution to the future prediction and evaluation of mineral resources.

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Authors and Affiliations

  1. MNR Key Laboratory of Metallogeny and Mineral Resource Assessment, Institute of Mineral Resources, Chinese Academy of Geological Sciences, Beijing, 100037, China

    Keyan Xiao, Mingjing Fan & Yang Xu

  2. International Mining Research Center, China Geological Survey, Beijing, 100037, China

    Jie Xiang

  3. China Mining News, China Geological Survey, Beijing, 100037, China

    Jie Xiang

  4. Institute of Geological Survey, China University of Geosciences, Wuhan, 430074, China

    Mingjing Fan

  5. China University of Geosciences, Beijing, 100083, China

    Yang Xu

Authors
  1. Keyan Xiao
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  2. Jie Xiang
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  3. Mingjing Fan
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  4. Yang Xu
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Corresponding author

Correspondence to Jie Xiang.

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Acknowledgments

This research was financially supported by the National Natural Science Foundation of China (No. 42002298), the National Key Research and Development Program of China (No. 2017YFC0601501), China Geological Survey (No. DD20201181), and the Open Research Fund Program of the Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring (Central South University), Ministry of Education (No. 2020YSJS09). The final publication is available at Springer via https://doi.org/10.1007/s12583-021-1437-8.

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Xiao, K., Xiang, J., Fan, M. et al. 3D Mineral Prospectivity Mapping Based on Deep Metallogenic Prediction Theory: A Case Study of the Lala Copper Mine, Sichuan, China. J. Earth Sci. 32, 348–357 (2021). https://doi.org/10.1007/s12583-021-1437-8

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