A deposit scale mineral prospectivity analysis: A comparison of various knowledge-driven approaches for porphyry copper targeting in Seridune, Iran. (April 2017)

• Record Type: Journal Article
• Authors: Abedi, Maysam; Mostafavi Kashani, Seyed Bagher; Norouzi, Gholam-Hossain; Yousefi, Mahyar
• Is Part Of: Journal of African earth sciences. Volume 128(2017)
• Page Start: 127
• Page End: 146
• Publication Date: 2017-04
• Subjects: Geological layers -- Electrical layers -- Magnetic layers -- Geochemical layer -- Porphyry copper -- Evidential belief functions -- Various outranking methods; Earth sciences -- Africa -- Periodicals; Earth sciences -- Middle East -- Periodicals; Geology -- Africa -- Periodicals; Geology -- Middle East -- Periodicals; Sciences de la terre -- Afrique -- Périodiques; Sciences de la terre -- Moyen-Orient -- Périodiques; Géologie -- Afrique -- Périodiques; Géologie -- Moyen-Orient -- Périodiques; Earth sciences; Geology; Africa; Middle East; Periodicals; Electronic journals; 556.05
• DOI: 10.1016/j.jafrearsci.2016.09.028
• Languages: English
• ISSNs: 1464-343X

Abstract

Abstract: In this paper, an application of a knowledge-driven mineral prospectivity mapping (MPM) approach so-called "the evidential belief functions (EBFs) using Dempster-Shafer's rule of combination" is proposed. This technique is used to weight and integrate a large scale exploration dataset in order to localize prospects for definition of further exploration drilling sites. In this study, exploration datasets of Seridune copper deposit in the Kerman province, SE Iran used for the methodology. In this regard, geophysical evidence layers extracted from interpretation of magnetic and electrical surveys, geological evidence layers derived via the geological datasets (i.e. lithology, fault and alteration), and geochemical evidence maps were generated and integrated for MPM. Furthermore, various MPM approaches including outranking, index overlay and fuzzy logic methods were examined for comparison with the introduced method. To evaluate and compare the efficiency of the methods, the productivity of the drilled boreholes (Cu concentration multiplied by its ore thickness along each drilled borehole) was used to validate the generated prospectivity models. The results showed higher efficiency of the Dempster-Shafer's model in comparison with the prospectivity models generated using other MPM approaches. Highlights: The EBFs using Dempster-Shafer's rule of combination is applied. The outranking, index overlay and fuzzy logic methods are examined for MPM. The productivity of the drilled boreholes is used to validate the generated MPMs. Higher efficiency of the Dempster-Shafer's model is reported.