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

Keyan Xiao; Jie Xiang; Mingjing Fan; Yang Xu

doi:10.1007/s12583-021-1437-8

Volume 32 Issue 2

Apr 2021

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Journal of Earth Science > 2021 > 32(2): 348-357.

Keyan Xiao, Jie Xiang, Mingjing Fan, Yang Xu. 3D Mineral Prospectivity Mapping Based on Deep Metallogenic Prediction Theory: A Case Study of the Lala Copper Mine, Sichuan, China. Journal of Earth Science, 2021, 32(2): 348-357. doi: 10.1007/s12583-021-1437-8

Citation:

Keyan Xiao, Jie Xiang, Mingjing Fan, Yang Xu. 3D Mineral Prospectivity Mapping Based on Deep Metallogenic Prediction Theory: A Case Study of the Lala Copper Mine, Sichuan, China. Journal of Earth Science, 2021, 32(2): 348-357. doi: 10.1007/s12583-021-1437-8

Citation:

Keyan Xiao, Jie Xiang, Mingjing Fan, Yang Xu. 3D Mineral Prospectivity Mapping Based on Deep Metallogenic Prediction Theory: A Case Study of the Lala Copper Mine, Sichuan, China. Journal of Earth Science, 2021, 32(2): 348-357. doi: 10.1007/s12583-021-1437-8

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

doi: 10.1007/s12583-021-1437-8

Keyan Xiao^1
,,
Jie Xiang^{2, 3
,
,
,},
Mingjing Fan^{1, 4},
Yang Xu^{1, 5}

1.
MNR Key Laboratory of Metallogeny and Mineral Resource Assessment, Institute of Mineral Resources, Chinese Academy of Geological Sciences, Beijing 100037, China
2.
International Mining Research Center, China Geological Survey, Beijing 100037, China
3.
China Mining News, China Geological Survey, Beijing 100037, China
4.
Institute of Geological Survey, China University of Geosciences, Wuhan 430074, China
5.
China University of Geosciences, Beijing 100083, China

More Information

Corresponding author: Jie Xiang, xiangjie@cugb.edu.cn
Received Date: 30 Nov 2020
Accepted Date: 20 Feb 2021
Publish Date: 01 Apr 2021

Abstract

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.
- deep mine resources,
- prospectivity mapping,
- 3D modeling,
- quantitative evaluation,
- Lala copper mine

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References(40)

References

Antoni, C., Eduardo, G. P., Lisard, T., et al., 2017. Mesozoic Volcanogenic Massive Sulfide (VMS) Deposits in Mexico. Ore Geology Reviews, 81: 1066-1083. https://doi.org/10.1016/j.oregeorev.2015.07.027

Carranza, E. J. M., 2009. Controls on Mineral Deposit Occurrence Inferred from Analysis of Their Spatial Pattern and Spatial Association with Geological Features. Ore Geology Reviews, 35(3/4): 383-400. https://doi.org/10.1016/j.oregeorev.2009.01.001

Chen, J. P., Lu, P., Wu, W., et al., 2007. A 3-D Prediction Method for Blind Orebody Based on 3-D Visualization Model and Its Application. Earth Science Frontiers, 14(5): 54-61. https://doi.org/10.1016/s1872-5791(07)60035-9

Chen, J. P., Yu, P. P., Shi, R., et al., 2014. Research on Three-Dimensional Quantitative Prediction and Evaluation Methods of Regional Concealed Ore Bodies. Earth Science Frontiers, 21(5): 211-220(in Chinese with English Abstract) http://en.cnki.com.cn/Article_en/CJFDTOTAL-DXQY201405020.htm

Chen, J. P., Xiang, J., Hu, Q., et al., 2016. Quantitative Geoscience and Geological Big Data Development: A Review. Acta Geologica Sinica——English Edition, 90(4): 1490-1515. https://doi.org/10.1111/1755-6724.12782

Gao, X. R., Wang, A. J., 2010. The Prediction of China's Steel Demand Based on S-Shaped Regularity. Acta Geoscientica Sinica, 31(5): 645-652(in Chinese with English Abstract) http://www.oalib.com/paper/1559733

Hagemann, S. G., Lisitsin, V. A., Huston, D. L., 2016. Mineral System Analysis: Quo Vadis. Ore Geology Reviews, 76(3): 504-522. https://doi.org/10.1016/j.oregeorev.2015.12.012

Li, N., Bagas, L., Li, X. H., et al., 2016. An Improved Buffer Analysis Technique for Model-Based 3D Mineral Potential Mapping and Its Application. Ore Geology Reviews, 76(2-3): 94-107. https://doi.org/10.1016/j.oregeorev.2015.12.002

Li, N., Song, X. L., Xiao, K. Y., et al., 2018. Part Ⅱ: A Demonstration of Integrating Multiple-Scale 3D Modelling into GIS-Based Prospectivity Analysis: A Case Study of the Huayuan-Malichang District, China. Ore Geology Reviews, 95(1-4): 292-305. https://doi.org/10.1016/j.oregeorev.2018.02.034

Li, R. S., 1996. Theory and Practice of Metallogenic System Analysis. Geological Publishing House, Beijing (in Chinese)

Li, X. H., Yuan, F., Zhang, M. M., et al., 2015. Three-Dimensional Mineral Prospectivity Modeling for Targeting of Concealed Mineralization within the Zhonggu Iron Orefield, Ningwu Basin, China. Ore Geology Reviews, 71(5): 633-654. https://doi.org/10.1016/j.oregeorev.2015.06.001

Liang, X., Liu, S. G., Wang, S. B., et al., 2019. Analysis of the Oldest Carbonate Gas Reservoir in China-New Geological Significance of the Dengying Gas Reservoir in the Weiyuan Structure, Sichuan Basin. Journal of Earth Science, 30(2): 348-366. https://doi.org/10.1007/s12583-017-0962-y

Liu, H., Tan, X. C., Li, L., et al., 2019. Eogenetic Karst in Interbedded Carbonates and Evaporites and Its Impact on Hydrocarbon Reservoir: A New Case from Middle Triassic Leikoupo Formation in Sichuan Basin, Southwest China. Journal of Earth Science, 30(5): 908-923. https://doi.org/10.1007/s12583-019-0888-7

Liu, S. G., Deng, B., Jansa, L., et al., 2018. Multi-Stage Basin Development and Hydrocarbon Accumulations: A Review of the Sichuan Basin at Eastern Margin of the Tibetan Plateau. Journal of Earth Science, 29(2): 307-325. https://doi.org/10.1007/s12583-017-0904-8

Mao, X. C., 2010. 3D Visualization Prediction of Concealed Ore Bodies. Central South University Press, Changsha (in Chinese)

Mao, X. C., Chen, J., Deng, H., et al., 2014. 3D Quantitative Predictivity of Concealed Ore Bodies in Fenghuangshan Copper Deposit, Tongling District, China. Acta Geologica Sinica——English Edition, 88(s2): 454-456. https://doi.org/10.1111/1755-6724.12373_20

Mao, X. C., Dai, T. G., Wu, X. B., 2009. The Stereoscopic Quantitative Prediction of Concealed Ore Bodies in the Deep and Marginal Parts of Crisis Mines: A Case Study of the Dachang Tin Polymetallic Ore Deposit in Guangxi. Geology in China, 36(2): 424-435(in Chinese with English Abstract) http://en.cnki.com.cn/Article_en/CJFDTOTAL-DIZI200902017.htm

Ouyang, Y., Liu, H. H., Wang, X., et al., 2019. Spatial Distribution Prediction of Laterite Bauxite in Bolaven Plateau Using GIS. Journal of Earth Science, 30(5): 1010-1019. https://doi.org/10.1007/s12583-019-1234-9

Sun, Y., Li, C. D., 1990. Mineralization Mechanism of Lala Copper Deposit in Sichuan Province. Journal of Chengdu College of Geology, 17(4): 1-9(in Chinese with English Abstract) http://en.cnki.com.cn/Article_en/CJFDTOTAL-CDLG199004000.htm

Tang, J. X., Deng, S. L., Zheng, W. B., 2011. An exploration Model for Jiama Copper Polymetallic Deposit in Maizhokunggar County, Tibet. Mineral Deposits, 30(2): 179-196(in Chinese with English Abstract) http://www.cqvip.com/QK/93610X/201102/37482866.html

Wang, D. H., Tang, J. X., Ying, L. J., 2010. Application of "Five Levels+Basement" Model for Prospecting Deposits into Depth. Journal of Jilin University (Earth Science Edition), 40(4): 733-738(in Chinese with English Abstract) http://www.zhangqiaokeyan.com/academic-journal-cn_journal-jilin-university-earth-science-edition_thesis/0201247972302.html

Wang, G. W., Li, R. X., Carranza, E. J. M., et al., 2015. 3D Geological Modeling for Prediction of Subsurface Mo Targets in the Luanchuan District, China. Ore Geology Reviews, 71(1-4): 592-610. https://doi.org/10.1016/j.oregeorev.2015.03.002

Wang, G. W., Zhang, S. T., Yan, C. H., et al., 2011. Mineral Potential Targeting and Resource Assessment Based on 3D Geological Modeling in Luanchuan Region, China. Computers & Geosciences, 37(12): 1976-1988. https://doi.org/10.1016/j.cageo.2011.05.007

Wang, S. C., 2010. The New Development of Theory and Method of Synthetic Information Mineral Resources Prognosis. Geological Bulletin of China, 29(10): 1399-1403(in Chinese with English Abstract) http://en.cnki.com.cn/Article_en/CJFDTOTAL-ZQYD201010003.htm

Wyborn, L. A. I., Heinrich, C. A., Jauqes, A. L., 1994. Australian Proterozoic Mineral Systems: Essential Ingredients and Mappable Criteria. Journal of the City Planning Institute of Japan, 5(94): 109-115 http://www.researchgate.net/publication/263884864_Australian_Proterozoic_mineral_systems_essential_ingredients_and_mappable_criteria

Xiang, J., Chen, J. P., Bagas, L., et al., 2020. Southern China's Manganese Resource Assessment: An Overview of Resource Status, Mineral System, and Prediction Model. Ore Geology Reviews, 116: 103261. https://doi.org/10.1016/j.oregeorev.2019.103261

Xiang, J., Xiao, K. Y., Carranza, E. J. M., et al., 2019. 3D Mineral Prospectivity Mapping with Random Forests: A Case Study of Tongling, Anhui, China. Natural Resources Research, 29(1): 395-414. https://doi.org/10.1007/s11053-019-09578-2

Xiao, K. Y., Cheng, S. L., Lou, D. B., 2010. Integrated Information Evaluation Model for Regional Mineral Resources Quantitative Assessment. Geological Bulletin of China, 29(10): 1430-1444(in Chinese with English Abstract) http://en.cnki.com.cn/Article_en/CJFDTOTAL-ZQYD201010006.htm

Xiao, K. Y., Li, N., Porwal, A., et al., 2015. GIS-Based 3D Prospectivity Mapping: A Case Study of Jiama Copper-Polymetallic Deposit in Tibet, China. Ore Geology Reviews, 71(11): 611-632. https://doi.org/10.1016/j.oregeorev.2015.03.001

Xiao, K. Y., Li, N., Sun, L., et al., 2012. Large Scale 3D Mineral Prediction Methods and Channels Based on 3D Information Technology. Journal of Geology, 36(3): 229-236(in Chinese with English Abstract) http://www.researchgate.net/publication/289987146_Large_scale_3D_mineral_prediction_methods_and_channels_based_on_3D_information_technology

Xiao, K. Y., Lou, D. B., Sun, L., et al., 2013. Collected Model of Potential Evaluation for Important National Mineral Resources in China. Journal of Geology, 37(3): 341-348(in Chinese with English Abstract) http://en.cnki.com.cn/Article_en/CJFDTOTAL-JSDZ201303001.htm

Xiao, K. Y., Zhao, P. D., 1994. A Prelimnary Discussion on Basic Problems and Reseaching Progermming of the Large Scale Metallogenetic Prognosis. Geological Exploration for Non-Ferrous Metals, 1: 49-56(in Chinese with English Abstract) http://en.cnki.com.cn/Article_en/CJFDTOTAL-YSJS401.012.htm

Yousefi, M., Kreuzer, O. P., Nykänen, V., et al., 2019. Exploration Information Systems——A Proposal for the Future Use of GIS in Mineral Exploration Targeting. Ore Geology Reviews, 111(3): 103005. https://doi.org/10.1016/j.oregeorev.2019.103005

Yuan, F., Li, X. H., Zhang, M. M., 2014. Three Dimension Prospectivity Modelling Based on Integrated Geoinformation for Prediction of Buried Ore Bodies. Acta Geologica Sinica, 88(4): 630-643(in Chinese with English Abstract) http://en.cnki.com.cn/Article_en/CJFDTOTAL-DZXE201404016.htm

Zhai, Y. S., 1999. On the Metallogenic System. Earth Science Frontiers, 6(1): 13-27(in Chinese with English Abstract)

Zhang, W. P., Yu, C., Li, F., et al., 2016. Geological Characteristics and Ore-Controlling Factors of Hongnipo Copper Deposit in Huili of Sichuan. Nonferrous Metals Engineering, 6(2): 80-84(in Chinese with English Abstract) http://en.cnki.com.cn/Article_en/CJFDTOTAL-YOUS201602019.htm

Zhao, P. D., Hu, W. L., 1992. Geological Anomaly Theory and Mineral Resource Prognosis. Xinjiang Geology, 10(2): 93-100(in Chinese with English Abstract) http://en.cnki.com.cn/Article_en/CJFDTOTAL-XJDI199202000.htm

Zhao, P. D., Li, Z. J., 1992. Statistical Prediction of Three-Dimensional Deposits in Key Metallogenic Regions: A Case Study of Yueshan Area, Anhui Province. China University of Geosciences Press, Wuhan (in Chinese)

Zhu, Y. S., 2006. Basic Theory of Mineral Resources Assessment-Theory System between Regional Metallogeny to Mineral Exporation. Acte Geologicasinica, 80(10): 1518-1527(in Chinese with English Abstract) http://www.researchgate.net/publication/291851694_Basic_theory_of_mineral_resources_assessment_-_Theory_system_between_regional_metallogeny_to_mineral_exporation

Zuo, R. G., 2020. Geodata Science-Based Mineral Prospectivity Mapping: A Review. Natural Resources Research, 29(6): 3415-3424. https://doi.org/10.1007/s11053-020-09700-9

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

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