Application of Best-Worst Method and Additive Ratio Assessment in Mineral Prospectivity Mapping: A Case Study of Vein-Type Copper Mineralization in the Kuhsiah-e-Urmak Area, Iran

Abstract This study proposes the application of a hybrid methodology combining the Best-Worst Method (BWM) and Additive Ratio Assessment (ARAS) approaches to mineral prospectivity mapping. The ARAS approach is used to prioritize and rank individual cells. The BWM, on the other hand, is useful for assigning weights to the spatial proxies of the mineralized system, representing mappable expressions of the ore-forming processes. A dataset of vein-type copper mineralization, including geochemical, geophysical, geological, and remotely sensed data from the Kuhsiah-e-Urmak area, Iran, was translated into a set of mappable spatial proxies representing the genetic processes involved in the formation of the vein-type copper mineralization. A hybrid BWM-ARAS method was applied to the spatial proxies used to generate the mineral potential map. The results of the proposed methodology were statistically compared to those obtained from the Index Overlay and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods using the rate of correct classification in confusion matrices and demonstrating the superiority of the proposed methodology. A field trip was conducted to assess the most prospective target zones and to collect samples for analysis. The majority of these samples returned significant copper contents with copper ores observed in most of the polished sections prepared from these samples. Considering these results, the newly proposed BWM-ARAS approach appears to offer a viable alternative to the conventional methods applied to knowledge-driven mineral prospectivity mapping.