A multi-disciplinary and exploratory geospatial data set integration for porphyry copper prospectivity mapping in Kerman belt, Iran

Abstract

The Mineral Prospectivity Map (MPM) is a powerful tool for identifying target areas for the exploration of undiscovered mineral deposits. In this study, a knowledge-driven Index overlay technique was utilized to create the MPM on a regional scale. The complex distribution patterns of geological features associated with mineral deposits were mapped and correlations between these features and mineral deposits were revealed by integrating geological, geophysical, hydrothermal alteration, and fault density data layers. It was found that 23% of the study area was highly prospective, with 77% of the known porphyry copper occurrences located within this area. The normalized density was equal to 3.35, indicating a significant relationship between the known porphyry copper occurrences and their occupied area. The MPM also identified potential tracts outside the known mineralized areas that can be used for exploration and quantitative assessment of undiscovered resources. It is suggested that the MPM is a valuable tool for mineral exploration and could have significant implications for the mining industry.

Keywords

• index overlay
• kerman cenozoic magmatic belt
• mineral prospectivity map
• porphyry copper deposit
• prediction-area (p-a) plot