• Title of article

    Analysis and integration of geo-information to identify granitic intrusions as exploration targets in southeastern Yunnan District, China

  • Author/Authors

    Wang، نويسنده , , Wenlei and Zhao، نويسنده , , Jie and Cheng، نويسنده , , Qiuming، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2011
  • Pages
    12
  • From page
    1946
  • To page
    1957
  • Abstract
    Identifying granite intrusions in the southeastern mineral district of Yunnan (China) is an essential task in support of mineral exploration for sustaining Sn mineral resources in the area. That is because the Sn and Cu hydrothermal mineralizations in this district are associated with granite intrusions, as sources of both hydrothermal fluid and heat. In this paper, a new high-pass filter technique based on a singularity analysis was applied to gravity and aeromagnetic data to delineate local anomalies characterizing granite intrusions. A PCA was applied to stream sediment geochemical data of 39 trace elements and compounds to derive a new integrated geochemical variable representing an element association, indicating the presence of granite intrusions. This new integrated geochemical variable is positively correlated with K2O, Na2O, Al2O3, Zr, Th, U, and Sr and negatively correlated with MgO and Fe2O3. To further characterize the granite intrusions, PCA was applied to integrate the local gravity and aeromagnetic anomalies obtained through singularity analysis and the new integrated geochemical variable obtained through PCA. The results show that the presence of outcropping and buried granitic intrusions is indicated by the principal component with positive loadings on the integrated geochemical variable and gravity data singularity and negative loadings on aeromagnetic data singularity. The methodology proposed in this paper is useful and effective for geo-information extraction and for integration of multisource geo-information for predictive modeling in mineral exploration.
  • Keywords
    Singularity , PCA , fractal , Information Integration , Mineral resource exploration
  • Journal title
    Computers & Geosciences
  • Serial Year
    2011
  • Journal title
    Computers & Geosciences
  • Record number

    2288352