Document Type : Original Research Paper

Authors

1 Ph.D., Self-Sufficiency and Applied Research Center, Khatam-al Anbiya Construction Headquarters, Tehran, Iran

2 Ph.D., Faculty of Sciences, Ferdowsi University, Mashhad, Iran

Abstract

Gilsonite mineralization in Shak Meydan zone as the most prone zone of Iranian gilsonite mineralization was predominantly hosted by the anidrite part of Asmari Formation (Kalhor member) and Gachsaran Formation. To find the prospect areas of gilsonite mineralization in ShakMeydan zone, the zone was divided into three sub zones in which exploration studies were conducted. We first tried to determine lithologic units using remote sensing processing and to separate rock units using image processing technology. Next, we plotted a 3D structural modeling of the study zone in order to increase the depth precision and to determine the stratigraphic sequence and stratigraphy-structural adaptation. Finally, we detected structural controllers including faults and existing breaks in each sub zone and circular structures prone to translocate minerals. In the sequel, we assigned appropriate weights to applied information layers including geological, tectonic, mineral information and the results of remote sensing studies using analytical hierarchy process (AHP) based on Knowledgeable information and field studies to synthesized the exploratory data in order to introduce the prospect areas with exploration priority.

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References
Bordenave, M. L. and Hegre, J. A., 2010- Current distribution of oil and gas fields in the Zagros Fold Belt of Iran and contiguous offshore as the result of the petroleum systems. In: Leturmy, P., Robin, C. (Eds.), Tectonic and Stratigraphic Evolution of Zagros and Makran during the Mesozoic-cenozoic, Geological Society, pp. 291- 353.
Cheng, Q., Chen, Z. and Khaled, A., 2007- Application of fuzzy weights of evidence methodin mineral resource assessment for goldin Zhenyuan District, Yunnan Province,China, Earth Science - Journal of China University of Geosciences, v. 32 (2), pp. 175- 184 (In Chinese with English Abstract).
El-Sawy, K., Ibrahim, A. M., El-Bastawesy, M. A. and El-Saud, W. A., 2016- Automated, manual lineaments extraction and geospatial analysis for Cairo-Suez district (Northeastern Cairo-Egypt), using remote sensing and GIS, International Journal of Innovative Science, Engineering & Technology, v. 3, pp. 2348- 7968.
Floyd, F. and Sabins, Z., 1999- Remote sensing for mineral exploration) Remote Sensing Enterprises, Celeste Lane, Fullerton, CA, USA, Ore Geology Reviews, v. 14, pp. 157- 183.
Hajibapir, G., Lotfi, M., Zarifi, A. Z. and Nezafati, N., 2014- Application of Different Image Processing Techniques on Aster and ETM+ Images for Exploration of Hydrothermal Alteration Associated with Copper Mineralizations Mapping Kehdolan Area (Eastern Azarbaijan Province-Iran), Journal of Geology, v. 4, pp. 582- 597.
Hosseini, S. A. and Abedi, M., 2015- Data EnvelopmentAnalysis:Aknowledge-drivenmethodformineral prospectivity mapping, Computers &Geosciences, v. 82, pp. 111- 119.
Kalinowski, A. and Oliver, S., 2004- ASTER Mineral Index Processing Manual Compiled by Remote Sensing Applications Geoscience, Australia, Center of Geographic Sciences.
Malczewski, J., 1999- GIS and multicriteria decision analysis, John Wiley and Sons, USA, 392 p.
Meyer, R. F. and De Witt, W. J., 1990- Definition and World Resources of Natural Bitumens, U. S. Geological Survey Bulletin 1944, 14 p.
Thenkabail, P. S., 2015- Remote Sensing Handbook, CRC Press, USA, 2200 p.
Verbeek, E. R. and Grout, M. A., 1993- Geometry and Structural Evolution of Gilsonite Dikes in the Eastern Uinta Basin, Utah, U. S. Geological Survey Bulletin 1787-HH, Reston, 52 p.
Zhang, N., Zhou, K. and Du, X., 2017- Application of fuzzy logic and fuzzy AHP to mineral prospectivity mapping of porphyry and hydrothermal vein copper deposits in the Dananhu-Tousuquan island arc, Xinjiang, NW China, Journal of African Earth Sciences, v. 128, pp. 84- 96.