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

  • Authors:

  • Wenlei Wang;Jie Zhao;Qiuming Cheng

  • Affiliations:

  • Department of Earth and Space Science and Engineering, Department of Geography, York University, 4700 Keele Street, Toronto, Ontario, Canada M3J 1P3;Department of Earth and Space Science and Engineering, Department of Geography, York University, 4700 Keele Street, Toronto, Ontario, Canada M3J 1P3;Department of Earth and Space Science and Engineering, Department of Geography, York University, 4700 Keele Street, Toronto, Ontario, Canada M3J 1P3 and State Key Lab of Geological Processes and M ...

  • Venue:
  • Computers & Geosciences
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

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 K"2O, Na"2O, Al"2O"3, Zr, Th, U, and Sr and negatively correlated with MgO and Fe"2O"3. 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.