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<p>This paper aims to map the promising anomalous areas of copper (Cu) mineralization using eight Multiple Attribute Decision Making (MADM) methods. Therefore, eight MADM methods, including SAW, TOPSIS, Taxonomy, PROMETHEE, VIKOR, COPRAS, WASPAS and MOORA, were used for mineral prospecting mapping (MPM). First, the geophysical, geochemical, and geological data were identified as the main criteria so that the geophysical criterion included two sub-criteria of magnetic and induced polarization (IP) data. The geochemical criterion included eight sub-criteria, including the element concentrations of Cu, Au, Mo, Ag, Pb, Zn, Mn and Se, and the geological criterion included three sub-criteria of heat source, host rock and alteration. Furthermore, the classification and scoring of each of the above sub-criteria were assigned scores of 1, 4, 7 and 10. Then, the decision matrix was formed for 13 sub-criteria and 82 samples as a matrix of 82*13 dimensions. In addition, the relative importance of the sub-criteria was determined based on the opinions of three experts, and the final weight of each was obtained. Then, the algorithms of the eight above methods were implemented, and the final score, as mineral prospectivity index (MPI), was calculated for each of the 82 alternatives (sampling points), with values between 0 and 1, and the final score of each point was indicated. The MPI values were then used as a parameter to determine the anomaly intensity at different points. Finally, the MPMs of the study area were generated in ArcGIS 10.5 software, and the results were compared.</p>

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The Copper Anomaly Detection Based on Geological, Geochemical and Geophysical Data Using Eight Proposed MADM Algorithms

  • 期刊论文

  • 发表日期：

    2025年11月14日

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  • Farzad Moradpouri,
  • Mohammad Hayati

摘要

This paper aims to map the promising anomalous areas of copper (Cu) mineralization using eight Multiple Attribute Decision Making (MADM) methods. Therefore, eight MADM methods, including SAW, TOPSIS, Taxonomy, PROMETHEE, VIKOR, COPRAS, WASPAS and MOORA, were used for mineral prospecting mapping (MPM). First, the geophysical, geochemical, and geological data were identified as the main criteria so that the geophysical criterion included two sub-criteria of magnetic and induced polarization (IP) data. The geochemical criterion included eight sub-criteria, including the element concentrations of Cu, Au, Mo, Ag, Pb, Zn, Mn and Se, and the geological criterion included three sub-criteria of heat source, host rock and alteration. Furthermore, the classification and scoring of each of the above sub-criteria were assigned scores of 1, 4, 7 and 10. Then, the decision matrix was formed for 13 sub-criteria and 82 samples as a matrix of 82*13 dimensions. In addition, the relative importance of the sub-criteria was determined based on the opinions of three experts, and the final weight of each was obtained. Then, the algorithms of the eight above methods were implemented, and the final score, as mineral prospectivity index (MPI), was calculated for each of the 82 alternatives (sampling points), with values between 0 and 1, and the final score of each point was indicated. The MPI values were then used as a parameter to determine the anomaly intensity at different points. Finally, the MPMs of the study area were generated in ArcGIS 10.5 software, and the results were compared.