3D mineral exploration targeting with multi-dimensional geoscience datasets, Tongling Cu(-Au) District, China

Abstract

The Tongling Cu(-Au) district is the most important magma-skarn type Cu(-Au) polymetallic districts in the Middle-Lower Yangtze metallogenic belt of China. The previous studies in the Tongling Cu(Au) district compiled available digital geological, geochemical, geophysical, and remote sensing datasets. As the discovery of near-surface Cu(-Au) deposits becomes more and more difficult in the Tongling Cu(-Au) district, we face the challenge of exploring for blind mineral deposits in the subsurface. Three-dimensional (3D) mineral potential mapping can provide effective exploration targeting by integrating multi-source and multi-dimension geoscience datasets. In this paper, firstly, a 3D district-scale geological model was constructed from multiple geoscience datasets. Secondly, multi-level (0 m, −300 m, −600 m, −900 m, −1200 m) exploration criteria were extracted by spatial analyses. Thirdly, the weights-of-evidence method, discrete smooth interpolation, and ordinary kriging interpolation were used to integrate multi-level exploration criteria including two-dimensional (2D) surface geochemical and remote sensing data into a 3D posterior-probability model. Finally, the concentration-area and concentration-volume fractal methods were used to define posterior-probability thresholds to outline 2D and 3D targets, respectively. The results indicated that the integrating performance of ordinary kriging interpolation is better than that of discrete smooth interpolation in 3D posterior-probability modeling. The whole procedure yielded a series of high-potential Cu(-Au) targets. The methodology discussed here can be used in other magma-skarn districts in the world.