Volume 27 Issue 3
Jun.  2021
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Article Navigation >  Journal of Geomechanics  > 2021  >  27(3): 374-390
DENG Jun, ZHAN Mingguo, ZHOU Weijin, et al., 2021. Quantitative prediction of mineral resources in typical gold deposits in Guangxi, China using a fuzzy weights of evidence method. Journal of Geomechanics, 27 (3): 374-390. DOI: 10.12090/j.issn.1006-6616.2021.27.03.034
Citation: DENG Jun, ZHAN Mingguo, ZHOU Weijin, et al., 2021. Quantitative prediction of mineral resources in typical gold deposits in Guangxi, China using a fuzzy weights of evidence method. Journal of Geomechanics, 27 (3): 374-390. DOI: 10.12090/j.issn.1006-6616.2021.27.03.034
shu

Quantitative prediction of mineral resources in typical gold deposits in Guangxi, China using a fuzzy weights of evidence method

doi: 10.12090/j.issn.1006-6616.2021.27.03.034
  • 1.

    Guangxi Zhuang Antonomous Region Geological Survey Institute, Nanning 530023, Guangxi, China

  • 2.

    Guangxi Bureau of Geology & Mineral Resources, Nanning 530023, Guangxi, China

  • 3.

    Faculty of Earth Sciences, China University of Geosciences, Wuhan 430074, Hubei, China

Funds:  This research is financially supported by Talent Highland Project of Key Mineral Resources Deep Exploration in Guangxi (Notification of Organization Department in Guangxi, No.[2019]85, 2019-2023), Provincial Entrusted Project under China Geological Survey (Grant No.DD20190379-19), and Preliminary Work Project of Bureau of Geological and Mineral Exploration and Development in Guangxi Institute of Geological Survey (Comprehensive study of geology and mineral resources in Guangxi, No.[2019]06)
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  • Received: 2021-02-01
  • Revised: 2021-04-22
  • Published: 2021-06-28
    Abstract
  • Quantitative prediction of mineral resources based on multi-information fusion is the leading topic of resource potential prediction, in which the deep mining of different geological background information and geochemical data is the key problem and still challenging. In this study, we analyzed the spatial distribution characteristics of main metallogenic and associated elements such as Au, Ag, Mn, Cu, Pb, Zn, Sn and Sb in 60767 geochemical samples on the platforms like ArcGIS and GeoDAS, by summerzing the geological background information and metallogenic controlling factors of each tectonic unit in Guangxi. Based on the GeoDAS paltform, through IDW interpolation, S-A anomaly decomposition, principal component analysis and other technologies, the data from the layers with geochemical component element anomaly, gravity and aeromagnetic anomaly and the buffers at the intersection of magmatic rock and fault were used as the training points for the utilization of the fuzzy weights of evidence. A posteriori probability map was drawn up to delineate the favorable metallogenic areas for Carlin-type gold deposit and fracture zone altered gold deposit. This study is of great significance to the application of new metallogenic theories and evaluation techniques in the evaluation or zoning of mineral resources potential.

     

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