Mineral potential mapping of porphyry copper using a fuzzy inference system in the Kerman belt.

Articles in Press

Document Type : Research Article

Authors

1 Department of Mining Engineering, Tabriz University of Technology, Tabriz, Iran.

2 Sahand University of Technology

3 Department of Mining Engineering, Sahand University of Technology, Tabriz, Iran.

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

10.22034/anm.2025.22750.1664

Abstract

The implementation of mineral exploration operations is inherently expensive and time-consuming, often requiring extensive fieldwork, laboratory analysis, and the integration of diverse datasets. One effective strategy for optimizing resources and reducing costs is the application of mineral potential modeling (MPM), which aims to predict areas with higher probabilities of mineralization. MPM can be categorized as an information-driven decision-making process that synthesizes various geoscientific datasets—such as geological, geochemical, geophysical, remote sensing, and alteration data—each offering complementary insights into subsurface conditions.



In the present study, a fuzzy based approach is proposed to model the mineral potential for the exploration of porphyry copper deposits. The method integrates multiple exploration datasets including geophysical, geochemical, geological, and remote sensing layers. Initially, each thematic map was transformed through a fuzzification process using linguistic variables and trapezoidal membership functions to model the inherent uncertainty and ambiguity in boundary definitions between spatial features. These fuzzified layers were then integrated using a Mamdani-type fuzzy inference system (FIS) which enables the translation of expert knowledge into a rule-based system for predictive mapping.



To evaluate and validate the performance of the proposed fuzzy approach, a comparative analysis was conducted using the **modified TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)** method, a multi-criteria decision-making technique. Both models were assessed using **Prediction-Area (P-A) plots and Normalized Density metrics. The Normalized Density value for the modified TOPSIS approach was calculated as 4, while the proposed fuzzy logic approach yielded a significantly higher ND value of 6.14 indicating its superior predictive capability.



This enhanced performance suggests that the fuzzy-based model not only improves the accuracy of mineral potential maps but also offers greater flexibility for application under various geological scenarios. The ability to incorporate expert knowledge and handle data uncertainty makes the proposed method a robust and interpretable tool for mineral exploration targeting.

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Main Subjects

Journal of Analytical and Numerical Methods in Mining Engineering

Articles in Press, Accepted Manuscript
Available Online from 08 November 2025

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History

  • Receive Date: 04 February 2025
  • Revise Date: 01 October 2025
  • Accept Date: 08 November 2025

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