Identifying geochemical anomaly through spatially anisotropic singularity mapping: A case study from silver-gold deposit in Pangxidong district, SE China

Abstract

The anisotropic singularity analysis, also referred to as Spatially Weighted Singularity Mapping (SWSM), was developed by means of multifractal modeling and spatial weighting. The SWSM extends the application of the Ordinary Singularity Mapping (OSM) technique, which is spatially isotropic, to the anisotropic case. In this paper, the SWSM method was demonstrated in a case study where the geochemical anomaly associated with the silver-gold mineralization was identified through mapping the spatially anisotropic singularity of the pathfinder elements including Ag, Au, Cu, Pb, and Zn, to in Pangxidong district, south of the Qinzhou-Hangzhou Metallogenic Belt, SE China. Firstly, using the stream sediment geochemical data and spatial weighting factor linked to NE-trending ore-controlling fault system, the local anisotropic singularity index values (i.e. ϵ-values) were estimated for each of the five elements. Then, Principal Component Analysis (PCA) was applied to the ϵ-values to obtain comprehensive geochemical anomaly of the multiple element (i.e. PC1 scores). It appeared that the comprehensive geochemical anomaly has a better prediction efficiency with the discovered silver-gold occurrences than the one derived from the OSM-PCA approach (PCA applied to singularity index values estimated by the OSM technique). The performance tests were assessed by using the receiver operating characteristics as well as prediction-area plot and concentration-area fractal analysis methods. Finally, the student's t-static method was employed to determine the reasonable threshold values separating the geochemical anomaly and background. The student's t-values indicate that spatial correlation between the locations of the known silver-gold mineral deposits and the geochemical anomaly derived by the SWSM-PCA approach was much stronger than that of the geochemical anomaly derived by the OSM-PCA method. The geochemical anomalies delineated by the SWSM-PCA approach were considered to be the favorable target areas for exploration of similar undiscovered silver-gold polymetallic deposits. This study has demonstrated that the SWSM approach can incorporate the spatial anisotropic information (e.g. direction and range of spatial variability), which exhibits geological controlling features, into the singularity analysis of geo-variables in various geo-spatial datasets such as geochemical, geophysical and remote sensing data.