Geochemical prospectivity of Au mineralization through Concentration-Number fractal modelling and Prediction-Area plot: a case study in the east of Iran

Document Type : Research Paper

Authors

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

Abstract

Birjand region is located in South Khorasan province in the structural-magmatic zone of eastern Iran. This part of the Iranian plateau is the result of subduction during the Cenozoic and subsequent continental collisions. This region is known as important in terms of copper and gold mineralization for various geological reasons. This research aims to develop a map of Au geochemical potential. 1966 geochemical samples were collected in the study area, and a 20-element analysis was performed. After data pre-processing including correction of outlier data and data normalization, and through a graph from the fractal concentration-number (C-N) model to isolate different geochemical populations of Au, As, Sb, Hg, Bi, Mo, Sn, and W with Au targeting, a Prediction-area (P-A) graph was plotted for each variable to determine the weight of each geochemical indicator. The results show that after gold, with an ore prediction rate of 74% and specifying 26% of the studied district as mineralization-prone areas, arsenic with a prediction rate of 72% has covered 28% of the Birjand region as potential mineralization areas while Bismuth and Mercury with a prediction of 64% covered 36% of the Birjand region. In addition, a hybrid indicator map was prepared utilizing a multi-class index overlay method, where the potential geochemical areas were located further south and southeast of Birjand. In addition, there are favourable areas in the middle. Notably, the mineral potential map (MPM) has higher efficiency than any geochemical indicator, with an ore prediction rate of 88% and occupying 12% of the whole prospect area.

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Article Title [Persian]

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