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Three-Dimensional Prospectivity Modeling of Honghai Volcanogenic Massive Sulfide Cu–Zn Deposit, Eastern Tianshan, Northwestern China Using Weights of Evidence and Fuzzy Logic

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Abstract

Three-dimensional (3D) prospectivity modeling based on the weights of evidence and fuzzy logic methods was carried out for the Honghai volcanogenic massive sulfide Cu–Zn deposit in eastern Tianshan, northwestern China. A 3D geological model was constructed using geological maps, geological plans, cross sections, and boreholes. The geological model and metallogenic model of the Honghai deposit were used to generate 3D predictor maps. The weights of evidence method and fuzzy logic were then used to integrate the various predictor maps to create prospectivity maps. Capture efficiency curves were subsequently used to delineate high-prospectivity areas in the prospectivity maps. The weights of evidence method and fuzzy logic delineated 96.13% and 90.60%, respectively, of the known mineralization in the high-prospectivity areas, which occupied about 5.89% and 6.33% of the study area. Receiver operating characteristic (ROC) curves were used to evaluate the performance of the two methods, with both showing area under the curve values > 0.5, which indicates the effectiveness of both methods for 3D prospectivity modeling of the Honghai deposit. However, the weights of evidence method generally performed better than fuzzy logic for identification of the concealed and deep-seated Honghai deposit. Conversely, fuzzy logic exhibited better generalization capability. Based on the findings of this study, the high-prospectivity areas located in the south of the known orebody of the Honghai deposit should be considered as high-priority targets for future mineral exploration. This study aims to enable more effective delineation of concealed and deep-seated exploration targets in the Honghai deposit.

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Acknowledgements

This work was supported by Opening Subject of Key Laboratories in the Xinjiang Uygur Autonomous Region (grant no. 2018D04025), National Key Research and Development Program of China (grant no. 2018YFC0604006-4), Strategic Priority Research Program of the Chinese Academy of Sciences (grant no. XDA19030204), and Light of West China program of the China Academy of Science.

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  1. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Ürümqi, 830011, China

    Jintao Tao, Nannan Zhang & Jinyu Chang

  2. Xinjiang Key Laboratory of Mineral Resources and Digital Geology, Ürümqi, 830011, China

    Jintao Tao, Feng Yuan, Nannan Zhang & Jinyu Chang

  3. Xinjiang Research Center for Mineral Resources, Chinese Academy of Sciences, Ürümqi, 830011, China

    Jintao Tao, Nannan Zhang & Jinyu Chang

  4. University of Chinese Academy of Sciences, Beijing, 100049, China

    Jintao Tao, Nannan Zhang & Jinyu Chang

  5. School of Resources and Environmental Engineering, Hefei University of Technology, Hefei, 230009, China

    Feng Yuan

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Tao, J., Yuan, F., Zhang, N. et al. Three-Dimensional Prospectivity Modeling of Honghai Volcanogenic Massive Sulfide Cu–Zn Deposit, Eastern Tianshan, Northwestern China Using Weights of Evidence and Fuzzy Logic. Math Geosci 53, 131–162 (2021). https://doi.org/10.1007/s11004-019-09844-2

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