Investigating the alteration of igneous rocks in relation to bentonite mineral mapping using remote sensing data in Khor and Biabanak, central Iran

Document Type : Research Paper

Authors

1 Department of Petroleum Engineering, Amirkabir University of Technology, Tehran, Iran.

2 Department of Mining Engineering, Isfahan University of Technology, Isfahan, Iran.

10.22059/ijmge.2025.383755.595202

Abstract

The alteration of igneous rocks indicates the formation and identification of valuable mineral deposits, such as bentonite, which is in increasing demand across various industries, including oil and steel. Remote sensing methods, leveraging the spectral characteristics of minerals, can detect hydrothermal alteration zones associated with various ore deposits, including bentonite, thereby reducing the cost of time and fieldwork. This study investigates the alteration of igneous rocks in the Khor and Biabanak region, located in the eastern part of Isfahan province, Iran, northeast of Nain city. Using ETM+ satellite data and field observations, we aimed to identify new potential bentonite resources. The ETM+ satellite data was processed using preprocessing stages including Layer Stacking, Subseting, Radiometric Corrections, Geometric Corrections, SLC-off Gap Filling, Noise Reduction (Destriping), Cloud and Water Masking, and Band Scaling/Normalization). This was followed by applying False Color Composite (FCC), Principal Component Analysis (PCA), the Enhanced Crosta technique, and the Least Squares Fitting (LS-Fit) method, which enabled us to identify promising mineral zones. Field surveys and X-ray Diffraction (XRD) analysis of samples confirmed significant concentrations of smectite (montmorillonite), indicative of substantial bentonite deposits. These findings suggest that integrating remote sensing techniques with field validation successfully identified areas with significant bentonite potential for further exploration. The successful application of these methods, particularly in a region with limited prior bentonite-focused remote sensing studies, highlights their utility in similar geological settings, offering a valuable approach for mineral exploration.

Keywords

Main Subjects


[1]. Oppenheimer C. SABINS, FF 1997. Remote Sensing. Principles and Interpretation, xiii+ 494 pp. New York: WH Freeman & Co. Price£ 32.95 (hard covers). ISBN 0 7167 2442 1. Geological Magazine. 1998;135(1):143-58.
[2]. MalekMahmoudi F. Mineralogical and geochemical studies of hydrothermal alteration and mineralization of altered zones in Tashtab Mount, Khur (North East of Isfahan): Isfahan University; 2010.
[3]. Marjoribanks R. Geological methods in mineral exploration and mining: Springer Science & Business Media; 2010.
[4]. Lamrani O, Aabi A, Boushaba A, Seghir MT, Adiri Z, Samaoui S. Bentonite clay minerals mapping using ASTER and field mineralogical data: a case study from the eastern Rif belt, Morocco. Remote Sensing Applications: Society and Environment. 2021;24:100640.
[5]. Van der Meer FD, Van der Werff HM, Van Ruitenbeek FJ, Hecker CA, Bakker WH, Noomen MF, et al. Multi-and hyperspectral geologic remote sensing: A review. International journal of applied Earth observation and geoinformation. 2012;14(1):112-28.
[6]. Saed S, Azizi H, Daneshvar N, Afzal P, Whattam SA, Mohammad YO. Hydrothermal alteration mapping using ASTER data, Takab-Baneh area, NW Iran: A key for further exploration of polymetal deposits. Geocarto International. 2022;37(26):11456-82.
[7]. Mirsepahvand F, Jafari M, Afzal P, Arian MA. Identification of Alteration Zones using ASTER Data for Metallic Mineralization in Ahar region, NW Iran. Journal of Mining and Environment. 2022;13(1):309-24.
[8].  Gholami R, Moradzadeh A, Yousefi M. Assessing the performance of independent component analysis in remote sensing data processing. Journal of the Indian Society of Remote Sensing. 2012;40:577-88.
[9]. Ciampalini A, Garfagnoli F, Del Ventisette C, Moretti S. Potential use of remote sensing techniques for exploration of iron deposits in Western Sahara and Southwest of Algeria. Natural resources research. 2013;22:179-90.
[10]. Gupta RP. Remote sensing geology: Springer; 2017.
[11]. Alimohammadi M, Alirezaei S, Kontak DJ. Application of ASTER data for exploration of porphyry copper deposits: A case study of Daraloo–Sarmeshk area, southern part of the Kerman copper belt, Iran. Ore geology reviews. 2015;70:290-304.
[12]. Amer R, El Mezayen A, Hasanein M. ASTER spectral analysis for alteration minerals associated with gold mineralization. Ore Geology Reviews. 2016;75:239-51.
[13]. Singh A, Harrison A. Standardized principal components. International journal of remote sensing. 1985;6(6):883-96.
[14]. Crosta A, De Souza Filho C, Azevedo F, Brodie C. Targeting key alteration minerals in epithermal deposits in Patagonia, Argentina, using ASTER imagery and principal component analysis. International journal of Remote sensing. 2003;24(21):4233-40.
[15]. Crosta AP, editor Enhancement of Landsat Thematic Mapper imagery for residual soil mapping in SW Minas Gerais State Brazil, a prospecting case history in greenstone belt terrain. Proceedings of the 7th ERIM Thematic Conference on Remote Sensing for Exploration Geology, 1989; 1989.
[16]. Loughlin W. Principal component analysis for alteration mapping. Photogrammetric Engineering and Remote Sensing. 1991;57(9):1163-9.
[17]. ESMAELZADEH KALKHORAN S, Ghannadpour SS, Jalili H, Moeini Rad A. Investigating porphyry copper alterations and spectral behavior of related minerals using ASTER satellite images in the Zafarghand region, Isfahan. Advanced Applied Geology. 2024;14(3):623-51.
[18]. Ghannadpour SS, Hasiri M, Jalili H, Talebiesfandarani S. Satellite Image Processing: Application for Alteration Separation based on U-Statistic Method in Zafarghand Porphyry System (Iran). Journal of Mining and Environment. 2024;15(2):667-81.
[19]. Ghannadpour SS, Esmailzadeh Kalkhoran S, Jalili H, Behifar M. Delineation of mineral potential zone using U-statistic method in processing satellite remote sensing images. International Journal of Mining and Geo-Engineering. 2023;57(4):445-53.
[20]. Ghannadpour SS, Hasiri M, Shahrabi HS, Jalili H. Mapping alteration zones associated with Cu mineralization: An approach based on image processing using the singularity method and fuzzy gamma operator. Kharazmi Journal of Earth Sciences. 2024;10(1):91-122.
[21]. Ghannadpour SS, Hasiri M, Jalili H, Salehi Shahrabi H. Identifying alterations of Zafarghand porphyry copper system (Isfahan): employing singularity method and false color composite. International Journal of Mining and Geo-Engineering. 2024;58(3):315-22.
[22]. Rothery D. Improved discrimination of rock units using Landsat Thematic Mapper imagery of the Oman ophiolite. Journal of the Geological Society. 1987;144(4):587-97.
[23]. Ghannadpour SS, Esmaelzadeh Kalkhoran S, Behifar M, Jalili H. Delineation of the alteration zones by CN fractal model on ASTER images. Journal of Mining and Environment. 2024.
[24]. Esmaelzadeh Kalkhoran S, Ghannadpour SS, Moeini Rad A, Jalili H. Comparing the performance of ASTER and LANDSAT 8 satellite images in identifying iron oxide and porphyry copper alterations in Zafarghand region of Isfahan province. Journal of Mineral Resources Engineering. 2024;9(1):41-65.
[25]. Pourgholam MM, Afzal P, Adib A, Rahbar K, Gholinejad M. Delineation of Iron alteration zones using spectrum-area fractal model and TOPSIS decision-making method in Tarom Metallogenic Zone, NW Iran. Journal of Mining and Environment. 2022;13(2):503-25.
[26]. Behbahanı B, Haratı H, Afzal P, Lotfı M. Determination of alteration zones applying fractal modeling and Spectral Feature Fitting (SFF) method in Saryazd porphyry copper system, central Iran. Bulletin of the Mineral Research and Exploration. 2023;172(172):1-14.