Document Type : Original Research Paper

Authors

1 M.Sc., Department of Mineral Exploration, Faculty of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran

2 Associte Professor, Department of Mineral Exploration, Faculty of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran

3 Assistant Professor, Department of Mining Engineering, Urmia University of Technology, Urmia, Iran

4 M.Sc., Geological Survey of Iran, Management of Northwestern Center, Tabriz, Iran

Abstract

The Khanik-Ghazan Titanium ore deposit is located at 82 km northwest of Urmia, northern Sanandaj-Sirjan zone. The main objective of this research is to identify potentially mineralized areas and to prepare a mineral prospectivity map in the Khanik-Ghazan deposit applying the Fuzzy Inference System (FIS). After preparing the facto maps, the main stages of the investigation comprise the preparation of fuzzy factor maps using the appropriate linguistic variables and proper membership functions, combining factor maps using the fuzzy inference (by creating a fuzzy database of If-OR rules), identification of susceptible areas, and the generation of a potential mineral map using the output closure. In this study, in order to control the accuracy of the data, we tried to apply two new integrated methods including the fuzzy logic and hierarchical analysis processes. The results obtained from these methods was confirmed and complemented by each other and demonstrated highly potential mineralized zones. This statement is validated by several investigation methods including the field surveys and evidence of 80 samples collected from rock outcrops. Based on obtained results and modelling of geophysical data, the central part of the study area was recognized for further exploration using the drillcore subsurface exploration.

Keywords

Main Subjects

References
Bonham-Carter. G., 1994- Geographic Information Systems for Geoscientists: Modelling with GIS. Pergamon, Ontario, Canada. 398.
Carranza, E. J., 2008- Geochemical anomaly and mineral prospectivity mapping in GIS. Handbook of Exploration and Environmental Geochemistry, vol. 11, Elsevier, Amsterdam, 351 p.
Carranza, E. M. and Hale, M., 2003- Evidential belief functions for geologically constrained mapping of gold potential, Baguio district, Philippines. Ore Geology. Rev. 22: 117-132.
Houshyar, E., Sheikh Davoodi, M. J., Almassi, M., Bahrami, H., Azadi, H., Omidi, M. and Witlox, F., 2014- Silage corn production in conventional and conservation tillage systems. Part I: sustainability analysis using combination of GIS/AHP and multi-fuzzy modeling. Ecological Indicators, 39, 102-114.
Karimi, M. and Valadan Zoej, M. J., 2004- Mineral potential mapping of copper minerals with GIS. Int Arch Photogramm Remote Sens Spatial Inf Sci, 35(4), 1103-1108.
Najafi, A., Karimpour, M. H. and Ghaderi, M., 2014- Application of fuzzy AHP method to IOCG prospectivity mapping: A case study in Taherabad prospecting area, astern Iran.  International Journal of Applied Earth Observation and Geoinformation :142-154.
Porwal, A., Carranza, E. and Hale, M., 2003- Artifcial neural networks for mineral-potential mapping: a case study from Aravalli Province, Western India, Natural Resources Research, 12: 156-171.
Porwal, A., Das, R. D., Chaudhary, B., Gonzalez-Alvarez, I. and Kreuzer, O., 2014- 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.
Saaty, T. L., 1990- Decision making for leaders: the analytic hierarchy process for decisions in a complex world- RWS publications Press, Pittsburgh.
Stocklin, J., 1968- Structural history and tectonics of Iran: a review. American Association of Petroleum Geology, Bull., 52: 1229-125.
Ying, H., 2000- Fuzzy control and modeling: analytical foundations and applications. Wiley-IEEE Press, 37(2), 125-128.
Zadeh, L. A., 1965- Fuzzy sets, Information and control. vol. 8, pp. 338-353.