Document Type : Original Research Paper


1 Department of Mining Engineering, Faculty of Engineering, Urmia University, Urmia, Iran

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


The Sonajil area is located in the east Azerbaijan province of Iran. According to studies on the geological structure, the region has experienced intrusive, subvolcanic, and extrusive magmatic activities, as well as subduction processes. As a result, the region is recognized for its high potential for mineralization, particularly for Cu-Au porphyry types. The main objective of this research work is to utilize the fuzzy gamma operator integration approach to identify the areas with high potential for porphyry deposits. To carry out this exploratory approach, it is necessary to investigate several indicator layers including geological, remote sensing, geochemical, and geo-physical data. The analysis reveals that the northeastern and southwestern parts of the Sonajil region exhibit a greater potential for porphyry deposits. The accuracy of the resulting Mineral Potential Map (MPM) in the Sonajil region was evaluated based on data from 20 drilled boreholes, which showed an agreement percentage of 83.33%. Due to the high level of agreement, certain locations identified in the generated MPM were recommended for further exploration studies and drilling.


Main Subjects

[1]. Carranza, E.J.M. and Hale, M. (2001). Geologically constrained fuzzy mapping of gold mineralization potential, Baguio district, Philippines. Natural Resources Research, 10, 125-136.
[2]. Porwal, A., Carranza, E.J.M., and Hale, M. (2003). Knowledge-driven and data-driven fuzzy models for predictive mineral potential mapping. Natural Resources Research, 12(1): 1-25.
[3]. Yousefi, M. and Carranza, E.J.M. (2015). Fuzzification of continuous-value spatial evidence for mineral prospectivity mapping. Computers & Geosciences, 74, 97-109.
[4]. Yousefi, M. and Carranza, E.J.M. (2017). Union score and fuzzy logic mineral prospectivity mapping using discretized and continuous spatial evidence values. Journal of African Earth Sciences, 128, 47-60.
[5]. Abedi, M., Kashani, S.B.M., Norouzi, G.H., and Yousefi, M. (2017). A deposit scale mineral prospectivity analysis: A comparison of various knowledge-driven approaches for porphyry copper targeting in Seridune, Iran. Journal of African Earth Sciences, 128, 127-146.
[6]. Ghasemzadeh, S., Maghsoudi, A., Yousefi, M., and Mihalasky, M.J. (2019). Stream sediment geochemical data analysis for district-scale mineral exploration targeting: Measuring the performance of the spatial U-statistic and CA fractal modeling. Ore Geology Reviews, 113, 103115.
[7]. Rahimi, H., Abedi, M., Yousefi, M., Bahroudi, A., and Elyasi, G. R. (2021). Supervised mineral exploration targeting and the challenges with the selection of deposit and non-deposit sites thereof. Applied Geochemistry, 128, 104940.
[8]. Khalifani, F., Imamalipour, A., Barak., S., Abedi, M., Jozanikohan, G., and Bahroudi, A., (2023). The Application of Various Mineral Prospectivity Modelingin the Exploration of Orogenic Gold Deposit in Saqez-Sardasht. Lithology and Mineral Resources, 58(4): 367-385.
[9]. Yousefi, M. and& Hronsky, J. M. (2023). Translation of the function of hydrothermal mineralization-related focused fluid flux into a mappable exploration criterion for mineral exploration targeting. Applied Geochemistry, 105561.
[10]. Porwal, A., Das, R.D., Chaudhary, B., Gonzalez-Alvarez, I., and Kreuzer, O. (2015). Fuzzy inference systems for prospectivity modeling of mineral systems and a case-study for prospectivity mapping of surficial Uranium in Yeelirrie Area, Western Australia. Ore Geology Reviews, 71, 839-852.
[11]. McCuaig, T.C., Beresford, S., and Hronsky, J. (2010). Translating the mineral systems approach into an effective exploration targeting system. Ore Geology Reviews, 38(3): 128-138.
[12]. Barak, S., Imamalipour, A., Abedi, M., Bahroudi, A., and Khalifani, F.M. (2021). Comprehensive modeling of mineral potential mapping by integration of multiset geosciences data. Geochemistry, 81(4): 125824.
[13]. Abedi, M. and Norouzi, G.H. (2012). Integration of various geophysical data with geological and geochemical data to determine additional drilling for copper exploration. Journal of Applied Geophysics, 83, 35-45.
[14]. Abedi, M., Norouzi, G.H., and Bahroudi, A. (2012). Support vector machine for multi classification of mineral prospectivity areas. Computers & Geosciences, 46, 272-283.
[15]. Barak, S., Bahroudi, A., and Jozanikohan, G. (2018a). Exploration of Sonajil porphyry copper deposit using advanced integration of geological, remote sensing, geochemical, and magnetics data. Journal of Mining and Environment, 9(1): 19-39.
[16]. Barak, S., Bahroudi, A., and Jozanikohan, G. (2018b). The use of fuzzy inference system in the integration of copper exploration layers in Neysian. Iranian Journal of Mining Engineering, 13(38): 97-112.
[17]. Barak, S., Abedi, M., and Bahroudi, A. (2020). A knowledge-guided fuzzy inference approach for integrating geophysics, geochemistry, and geology data in a deposit-scale porphyry copper targeting, Saveh, Iran. Bollettino di Geofisica Teorica ed Applicata, 61(2).
[18]. Ghaeminejad, H., Abedi, M., Afzal, P., Zaynali, F., and Yousefi, M. (2020). A fractal-based outranking approach for mineral prospectivity analysis. Bollettino di Geofisica Teorica e Applicata, 61(4): 555-588.
[19]. Panahi, S., Khakzad, A., and Afzal, P. (2022). Analytical hierarchical prospectivity mapping using integration of exploratory data in the Anarak region, Central Iran. Geopersia, 12(1): 53-68.
[20]. Zimmermann, H.J. (2010). Fuzzy set theory. Wiley interdisciplinary reviews: computational statistics, 2(3): 317-332.
[21]. Bonham-Carter, G.F. (1994). Geographic information systems for geoscientists-modeling with GIS. Computer methods in the geoscientists, 13, 398.
[22]. Carranza, E.J.M. (2008). Geochemical anomaly and mineral prospectivity mapping in GIS. Elsevier.
[23]. Tangestani, M.H. and Moore, F. (2003). Mapping porphyry copper potential with a fuzzy model, northern Shahr‐e‐Babak, Iran. Australian Journal of Earth Sciences, 50(3): 311-317.
[24]. Yazdi, Z., Rad, A.J., Aghazadeh, M., and Afzal, P. (2019). Porphyry copper prospectivity mapping using fuzzy and fractal modeling in sonajeel area, NW Iran. Bulletin of the Mineral Research and Exploration, 158(158): 235-250.
[25]. Yazdi, Z., Jafari Rad, A., Aghazadeh, M., and Afzal, P. (2018). Alteration mapping for porphyry copper exploration using ASTER and QuickBird multispectral images, Sonajeel Prospect, NW Iran. Journal of the Indian Society of Remote Sensing, 46, 1581-1593.
[26]. Dilek, Y., Imamverdiyev, N., and Altunkaynak, Ş. (2010). Geochemistry and tectonics of Cenozoic volcanism in the Lesser Caucasus (Azerbaijan) and the peri-Arabian region: collision-induced mantle dynamics and its magmatic fingerprint. International Geology Review, 52(4-6): 536-578.
[27]. Aghazadeh, M., Hou, Z., Badrzadeh, Z., and Zhou, L. (2015). Temporal–spatial distribution and tectonic setting of porphyry copper deposits in Iran: constraints from zircon U–Pb and molybdenite Re–Os geochronology. Ore geology reviews, 70, 385-406.
[28]. Jamali, H. and Mehrabi, B. (2015). Relationships between arc maturity and Cu–Mo–Au porphyry and related epithermal mineralization at the Cenozoic Arasbaran magmatic belt. Ore Geology Reviews, 65, 487-501.
[29]. Ghorbani, M. (2013). The economic geology of Iran. Mineral deposits and natural resources. Springer, 1-450.
[30]. Jamali, H., Yaghubpur, A., Mehrabi, B., Dilek, Y., Daliran, F., and Meshkani, A. (2012). Petrogenesis and tectono-magmatic setting of Meso-Cenozoic magmatism in Azerbaijan province, Northwestern Iran. Petrology–new perspectives and applications. Intech, 39-56.
[31]. Maghsoudi, A., Yazdi, M., Mehrpartou, M., Vosoughi, M., and Younesi, S. (2014). Porphyry Cu–Au mineralization in the Mirkuh Ali Mirza magmatic complex, NW Iran. Journal of Asian Earth Sciences, 79, 932-941.
[32]. KCE (Kavoshgaran Consulting Engineers), (2006), Report of lithogeochemical explorations in Sonajil region.
[33]. Hosseinzadeh, G.H., Mouayed, M., and Esfehanipour, R. (2009). Supergene processes in Sonajil porphyry copper deposit with respect to using of leached capping for estimation of supergene enrichment in porphyry copper deposits, 3(10): 85-96.
[34]. Sillitoe, R.H. (2010). Porphyry copper systems. Economic geology, 105(1): 3-41.
[35]. Barak, S., Bahroudi, A., Aslani, S., and Mohebi, A. (2016). The geochemical anomaly separation by using the soil samples of eastern of Neysian, Isfahan Province, Geochemistry, 5(1): 55–71.
[36]. Afzal, P., Jebeli, M., Pourkermani, M., and Jafari Rad, A. (2018). Correlation between rock types and Copper mineralization using fractal modeling in Kushk-e-Bahram deposit, Central Iran. Geopersia, 8(1): 131-141.
[37]. Afzal, P., Alghalandis, Y.F., Khakzad, A., Moarefvand, P., and Omran, N.R. (2011). Delineation of mineralization zones in porphyry Cu deposits by fractal concentration–volume modeling. Journal of Geochemical exploration, 108(3): 220-232.
[38]. Afzal, P., Zia Zarifi, A., and Sadeghi, B. (2013). Separation of geochemical anomalies using factor analysis and concentration-number (C.N.) fractal modeling based on stream sediments data in Esfordi 1: 100000 Sheet, Central Iran. Iranian Journal of Earth Sciences, 5(2): 100-110.
[39]. Hassanpour, S. and Afzal, P. (2013). Application of concentration–number (C–N) multifractal modeling for geochemical anomaly separation in Haftcheshmeh porphyry system, NW Iran. Arabian Journal of Geosciences, 6(3): 957-970.
[40]. Khalifani, F., Bahroudi, A., Barak, S., and Abedi, M. (2019). An integrated Fuzzy AHP-VIKOR method for gold potential mapping in Saqez prospecting zone, Iran. Earth Observation and Geomatics Engineering, 3(1): 21-33.
[41]. Ghasemzadeh, S., Maghsoudi, A., Yousefi, M., and Mihalasky, M. J. (2022). Information value-based geochemical anomaly modeling: A statistical index to generate enhanced geochemical signatures for mineral exploration targeting. Applied Geochemistry, 136, 105177.
[42]. Cannell, J., Cooke, D.R., Walshe, J.L., and Stein, H. (2005). Geology, mineralization, alteration, and structural evolution of the El Teniente porphyry Cu-Mo deposit. Economic Geology, 100(5): 979-1003.
[43]. Abrams, M.J., Brown, D., Lepley, L., and Sadowski, R. (1983). Remote sensing for porphyry copper deposits in southern Arizona. Economic Geology, 78(4): 591-604.
[44]. Tommaso, I. and Rubinstein, N. (2007). Hydrothermal alteration mapping using ASTER data in the Infiernillo porphyry deposit, Argentina. Ore Geology Reviews, 32(1-2): 275-290.
[45]. Ninomiya, Y. (2003, March). Rock type mapping with indices defined for multispectral thermal infrared ASTER data: case studies. In Remote Sensing for Environmental Monitoring, GIS Applications, and Geology II (Vol. 4886, pp. 123-132). SPIE.
[46]. Qin, J., Burks, T.F., Ritenour, M.A., and Bonn, W.G. (2009). Detection of citrus canker using hyperspectral reflectance imaging with spectral information divergence. Journal of food engineering, 93(2): 183-191.
[47]. Settle, J.J. and Drake, N. A. (1993). Linear mixing and the estimation of ground cover proportions. International Journal of Remote Sensing, 14(6): 1159-1177.
[48]. Scott, D.R. (1988). Effects of binary encoding on pattern recognition and library matching of spectral data. Chemometrics and intelligent laboratory systems, 4(1): 47-63.
[49]. Zadeh, L.A. (1965). Fuzzy sets. Information and control, 8(3): 338-353.