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

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 dataset...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of geochemical exploration 2021-02, Vol.221, p.106702, Article 106702
Hauptverfasser: Zhang, Zhiqiang, Wang, Gongwen, Ding, Yunna, Carranza, Emmanuel John M.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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. [Display omitted] •Geometrical modeling of CuAu deposits using multiple prospectivity mapping at five levels for 3D targeting•Fractal modeling for mineral targets classification and identification.•Kriging interpolation to construct a 3D potential mineral targeting
ISSN:0375-6742
1879-1689
DOI:10.1016/j.gexplo.2020.106702