A Hybrid Fuzzy Ordered Weighted Averaging Method in Mineral Prospectivity Mapping: a case for Porphyry Cu Exploration in Chahargonbad District, Iran

Document Type : Research Paper


School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran.



This research case study presents a fuzzy ordered weighted averaging (FOWA) method for mineral prospectivity/potential mapping (MPM) at Chahargonbad district in SE Iran, a system whereby new areas of high prospectivity for porphyry Cu mineralization are identified. The ultimate goal of this research is to find the complex and hidden relationships between the evidence layers and known ore occurrences using a comprehensive consideration of a multi-disciplinary geospatial data set. Hence, thirteen evidences are accurately derived from available databases, including geological, geochemical, geophysical, and remote sensing, and integrated through a FOWA multi-criteria decision-making approach to delineate favorable Cu-bearing zones. FOWA methodology uses a wide range of decision strategies to synthesize input geospatial evidences utilizing multiple values for an alpha parameter as the cornerstone of the algorithm that controls the experts' attitude toward the MPM risk. It is reflected through the generation of seven mineral potential maps to search the most suitable one(s). Considering a prediction-area plot for data-driven weight assignment of each evidence map, the hybrid FOWA outputs are searched for the most appropriate map in targeting notable Cu occurrences. The desired synthesized evidence map could indicate an ore prediction rate of 77%, where known Cu deposits were distributed at favorable zones occupying 23% of the whole district area. 


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