Presenting a mapping method based on fuzzy Logic and TOPSIS multi criteria decision-making methods to detect promising porphyry copper mineralization areas in the east of the Sarcheshmeh copper metallogenic district

زمین شناسی اقتصادی

Article 5, Volume 9, Issue 2 - Serial Number 17, November 2017, Pages 357-374   

Document Type: Research Article

DOI: 10.22067/econg.v9i2.45829

Authors

Shokouh Riahi^* ; Nader Fathianpour; Seyed Hassan Tabatabaei

Isfahan University of Technology

Abstract

Introduction
The growing demand for base metals such as iron, copper, lead and zinc on the one hand and the diminishing of surficial and shallow resources of these elements on the other hand have forced explorationists to focus on detecting deep deposits of these metals. As a result, the discovery of such deep deposits requires more advanced and sophisticated methods in the course of preliminary prospecting stages. Since the discovery of new deposits is getting to be increasingly difficult, deploying new prospecting technologies that employ more deposit attributes in the course of combining exploratory evidence may reduce the exploration costs with lower uncertainties. In the past two decades, a number of new data mining and integrating approaches capable of incorporating direct and indirect mineralization indicators, based on expert knowledge, data, or a combination of both, have been proposed )Bonham-Carter, 1994(. In the first step, the input exploratory data layers are corrected and validated through applying some statistical pre-processing algorithms such as background and outlier removal methods. In order to detect a mineralization occurrence, it is necessary to find the proper exploratory geological, geochemical and geophysical data layers which have direct or indirect associations with the governing mineralization followed by constructing these models in an appropriate GIS platform (Malkzewski, 1999). Due to the imperfect available data and a number of unknown parameters affecting the mineralization process, the application of conventional GIS integration methods such as Boolean or weighted overlay or even fuzzy logic methods alone may not produce appropriate results, pointing to a need for deploying multi-criteria decision-making methods such as TOPSIS. In the present study, the pre-processed exploratory data including geological, remotely sensed geophysical and geochemical imagery were used to detect favorable mineralization zones through applying the multi-criteria decision-making method. Finally, the selected favorable areas in the metallogenic strip located at the south to the south-east of the Sarcheshmeh porphyry copper deposit are prioritized and introduced for further follow up ground exploration operations.

Methodology
In order to solve complex decision-making problems like the problem of mapping favorable porphyry copper mineralization zones under great uncertainties, the TOPSIS method is considered as an appropriate approach offering significant simplicity, flexibility and capability (Ataei., 2010). The TOPSIS method is considered to be an efficient method due to having very high accuracy, speed, sensitivity as well as being easy to implement and interpret the outputted results (Hwang and Yoon, 1981). It has found many applications in important areas of mining industry where there is a need to make decisions under risky conditions and data uncertainties.
One basic issue in applying decision-making methods in the field of mineral exploration is to rank and propose the best possible candidates among all potentially favorable areas for the next stage of mineral exploration. In this regard, the best favorable areas are selected based on exploratory data layers including favorable lithologies, alterations, structures plus geochemical and geophysical anomalies (Pazand et al., 2012).

Results and discussion
In the first step, the area located south to the southeast of one the largest porphyry copper deposits in Iran known as Sarcheshmeh was investigated for favorable areas using all available exploratory data as mentioned in the previous section using fuzzy logic integration approach in the GIS environment.
Evaluating the highly favorable areas presented by the fuzzy logic approach showed great consistency with the already known copper mineralization prospects. Next, the first 20 priorities obtained from the fuzzy logic approach were chosen as the best candidates to be ranked using the TOPSIS multi criteria decision-making method. Among these favorable prospects, the one with the highest coefficient close to the ideal solution of 0.796 was found to be coincident with the Darehzar area that is a well known porphyry copper deposit 12 kilometers south of the Sarcheshmeh deposit.
The favorable areas numbered 5 and 8 that correspond to well known porphyry copper mineralization prospects called Sereydoon and North Sereydoon were ranked as the second and third priorities with scores of 0.721 and 0.604, respectively. Other favorable areas ranked by the TOPSIS method were also prioritized and presented for further follow up explorations.
To assess the sensitivity of the results obtained by the TOPSIS method, an amount of 10% of the values of each of the criteria were added and the outputted ranking results were compared to that of the original TOPSIS results. It was concluded that a slight change in the values of the criteria would not have significant impact on the results. However, 10 percent change of each criteria weight would greatly affect the prospects priorities obtained by re-applying the TOPSIS method.

References
Ataei, M., 2010. Multi Criteria Decision Making. Shahrood University Publications, Shahrood, 333 pp
Bonham–Carter, G.F., 1994. Geographic information system for geoscientists-molding with GIS. Geological Survey of Canada, Ontario, Canada, 398 pp.
Hwang, C.L. and Yoon, K., 1981; Multiple Attribute Decision Making: Methods and Applications, Springer-Verlag, Berlin, 228 pp.
Malkzewski, J., 1999, GIS and Multi Criteria Decision Analysis. John Whily and Sons, Canada, 387 pp.
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Keywords

mineral exploration; Fuzzy logic approach; TOPSIS method; porphyry copper mineralization; favorable regions

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