An enhanced strategy for geo-exploratory data analysis to facilitate the discovery of new mineral deposits

Abstract

The present study introduces an advanced strategy for analyzing geo-exploratory datasets for regions with limited exploration and research progress. Nonlinear techniques are utilized to scrutinize geological mapping and geochemical exploration data at a scale of 1:50,000 in the Zhule-Mangla district, Northern Tibet, China. To investigate the Cu mineralization associated with porphyry systems in this district, the local singularity analysis is applied to assess spatial variations in geochemical behaviors of the primary ore element (i.e., Cu). By interpreting a mesh-like pattern characterized by anomalies trending in the northeast and northwest directions, a comprehensive structural framework for the study region is established, thereby pinpointing potential areas of interest. Furthermore, multifractal analysis is applied to assess the distribution of Cu across both global and local scales. A novel multifractal parameter, termed the relative enrichment index H, is proposed as a specialized metric for evaluating the spatial distribution pattern of regional elements. The multifractal spectrum on a global scale serves as the foundation for examining all multifractal parameters on a local scale. This is achieved through an analysis of Cu concentrations within various geological units, revealing areas with accumulated ore materials that indicate potential mineralization. Ultimately, our analysis identifies four potential zones by jointly interpreting the insights derived from local singularity and multifractal analysis. These targets can be considered as reliable indicators for the subsequent stages of mineral exploration, facilitating a more thorough and comprehensive exploration process.