Advanced Search

Indexed by SCI、CA、РЖ、PA、CSA、ZR、etc .

Volume 32 Issue 2
Apr 2021
Turn off MathJax
Article Contents
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

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
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
  • 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.

     

  • loading
  • 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
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(5)  / Tables(1)

    Article Metrics

    Article views(434) PDF downloads(50) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return