Genetic Models of Porphyry Copper-Gold and IOCG Deposits Applied to Hybrid Data Integration Modelling in Central Iran

Generic genetic models of porphyry copper gold and iron oxide copper-gold (IOCG) deposits are used in conjunction with deposit models of the Dalli porphyry copper-gold deposit, Aftabru IOCG prospect and other less important Cu-Au deposits within the study area to identify recognition criteria for exploration targeting of Cu-Au deposits. The recognition criteria are represented in the form of GIS predictor layers (spatial proxies) by processing available geology, stream sediment geochemistry, airborne magnetics and multispectral remote sensing datasets. A hybrid "Adaptive Neuro Fuzzy Inference System" (ANFIS, Jang 1993) is implemented to map Cu-Au prospectivity of the Urumieh-Dokhtar magmatic arc (UDMA) in central Iran. An ANFIS is trained using 30 percent of the 61 known Cu-Au deposits in the area. In a parallel analysis, an exclusively expert-knowledge-driven fuzzy model was implemented using the same input predictor maps. The known and several unknown potential areas are mapped by both models. In the fuzzy analysis, the moderate and high favourable areas cover 16 percent of the study area, which predict 77 percent of the known copper-gold deposits. By comparison, in the neuro-fuzzy approach the moderate and high favorable areas cover 17 percent of the study area, which predict 82 percent of the Cu-Au deposits.