بررسی و تهیه نقشه پتانسیل مطلوب کانی سازی پنهان مس-طلادار پورفیری ورقههای یکصد هزارم بصیران و کودگان | |
| روش های تحلیلی و عددی در مهندسی معدن | |
| دوره 15، شماره 42، فروردین 1404، صفحه 37-50 اصل مقاله (1.19 M) | |
| نوع مقاله: مقاله پژوهشی | |
| شناسه دیجیتال (DOI): 10.22034/anm.2023.18917.1568 | |
| نویسندگان | |
| منصور ضیائی* 1؛ علی شبانی1؛ مهرداد سلیمانی منفرد1؛ عارف شیرازی2؛ سید امیر علی حامدی2 | |
| 1گروه معدن، دانشکده مهندسی معدن، نفت و ژئوفیزیک دانشگاه صنعتی شاهرود، شاهرود، ایران | |
| 2دانشکده مهندسی معدن، دانشگاه صنعتی امیرکبیر، تهران، ایران | |
| چکیده | |
| این مطالعه در کمربند متالوژنی قلعه زری - ده سلم متعلق به ورقه اصلی بصیران و کودگان صورت پذیرفت. نقشه پتانسیل مطلوب خاص ذخایر پنهان مس طلادار پورفیری با استفاده از دادههای ژئوشیمیایی رسوبات آبراههای، ساختاری، زمینشناسی و پراکندگی اندیسها تهیه شد. از روشهای ترکیبی زونالیته ژئوشیمیایی، سینگولاریتی و سلسله مراتبی فازی (AHP) استفاده گردید. در این تحقیق از روش کلان دادههای ژئوشیمیایی برای ارزیابی منظرهای ژئوشیمیایی خشک و کویری جهت آشکارسازی آنومالیهای پنهان و عمیق که دگرسانی ضعیف دارند استفاده گردید از 5200 کیلومترمربع 490 کیلومتر پتانسیل دار جدا شد و 17 اندیس از 22 اندیس کانی سازی شده در مناطق پتانسیل دار واقع شدهاند. | |
| کلیدواژهها | |
| زونالته؛ مس-طلا پورفیری؛ بصیران؛ کودگان؛ تلفیق سلسلهمراتبی؛ AHP | |
| عنوان مقاله [English] | |
| Mineral Prospectivity Mapping of the Hidden Cu-Au Porphyry Mineralization in the Basiran and Kodegan 1:100,000 Sheets | |
| نویسندگان [English] | |
| Mansour Ziaii1؛ Ali Shabani1؛ Mehrdad Soleimani Monfared1؛ Aref Shirazi2؛ Seyyed Amirali Hamedi2 | |
| 1Dept. of Mining, Faculty of Mining, Petroleum and Geophysical Engineering, Shahrood University of Technology, Shahrood, Iran | |
| 2Dept. of Mining Engineering, Amirkabir University of Technology, Tehran, Iran | |
| چکیده [English] | |
| Summary This study was carried out in the eastern area of the Lut block and sheets of Basiran and Kodegan. Due to the existence of numerous vein copper deposits in this area, the possibility of porphyry copper mineralization was evaluated by using the zonality indicators related to porphyry copper deposits and the singularity method, and tectonic and geological maps. In this research, after modifying the censored data, the histogram of the abundance of elements related to the used zonality index, including copper, lead, zinc, and molybdenum, was drawn, and after software processing of the data using logarithmic images of grade-area, the amount of anomalous grade and background. is identified. The dispersion map of lead, zinc, and copper elements was prepared and analyzed, and the dispersion elements were used as one of the weighting layers in the hierarchical integration method of AHP. Also, the distribution map of the index of supra-mineral and sub-mineral zonality was prepared, and by combining the two maps, the layer of areas rich in lead, zinc, copper, and molybdenum was obtained and used in the AHP method. The singularity method related to the surface production of the zonality index in windows with an area of 2,500 square meters was used to prepare one of the weighting layers in the hierarchical method. In the geological map of the region, the Oligo-Miocene intrusive masses were integrated as a suitable substrate for hosting copper deposits with the tectonic evidence layer and were used as one of the main weighting parameters in the AHP method. The use of the geological layer in the AHP matrix led to the removal of alluvial areas or Quaternary sediments in the detection of promising porphyry copper mineralization areas. The desired layers were combined with each other in the GIS software environment by the AHP add-on, and a favorable potential map for porphyry copper mineralization was prepared. In the final result of hierarchical integration, the area of 490 square kilometers out of 5200 square kilometers of the investigated area was introduced as a promising area. In this research, using quantitative variables, a qualitative and functional map was prepared to advance the preliminary explorations of the region. In order to validate the processing, 22 known mineral indices related to copper mineralization were used, of which 17 indices, equivalent to 77% of them, were found in the areas identified in this study. | |
| کلیدواژهها [English] | |
| Zonalte, Geochemistry, Basiran, Kodegan, Qala Zari, AHP | |
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[1] Ziaii, M. Lithogeochemical exploration methods for porphyry copper deposit in Sungun, NW Iran. Unpublished M. Sc. Thesis, Moscow State University (MSU), Moscow 1996, 98.
[2] Malekzadeh, A., Karimpour, M.H., Mazaheri, S.A., 2010b. Geology, alteration, mineralization and geochemistry of MA-II region, Maherabad porphyry copper-gold prospect area, South Khorasan province. Iranian Journal of Crystallography and Mineralogy. 639-654
[3] Carranza, E.J.M. Geochemical anomaly and mineral prospectivity mapping in GIS; Elsevier: 2008.
[4] Ziaii, M.; Carranza, E.J.M.; Ziaei, M. Application of geochemical zonality coefficients in mineral prospectivity mapping. Computers & geosciences 2011, 37, 1935-1945.
[5] Cooke, D.; Hollings, P.; Wilkinson, J.; Tosdal, R. Geochemistry of porphyry deposits. 2014.
[6] Ziaii, M.; Ardejani, F.D.; Ziaei, M.; Soleymani, A.A. Neuro-fuzzy modeling based genetic algorithms for identification of geochemical anomalies in mining geochemistry. Applied geochemistry 2012, 27, 663-676.
[7] Goldberg, I.; Abramson, G.Y.; Los, V. Depletion and enrichment of primary haloes: their importance in the genesis of and exploration for mineral deposits. Geochemistry: Exploration, Environment, Analysis 2003, 3, 281-293.
[8] Zuo, R.; Cheng, Q.; Agterberg, F.; Xia, Q. Application of singularity mapping technique to identify local anomalies using stream sediment geochemical data, a case study from Gangdese, Tibet, western China. Journal of Geochemical Exploration 2009, 101, 225-235.
[9] Safari, S.; Ziaii, M.; Ghoorchi, M. Integration of singularity and zonality methods for prospectivity map of blind mineralization. International Journal of Mining and Geo-Engineering 2016, 50, 189-194.
[10] Iran, G.S. Geochemical map report for Basiran and Kodegan 1:100,000 Map; 1992.
[11] Malekzadeh, A.; Karimpour, M.; Mazaheri, S. Geology, alteration, mineralization and geochemistry of MA-II region, Maherabad porphyry copper-gold prospect area, South Khorasan province. Iranian Journal of Crystallography and Mineralogy inpress 2010.
[12] Ghorbani, M. The economic geology of Iran. Mineral deposits and natural resources. Springer 2013, 1-450.
[13] Maghfouri, S.; Hosseinzadeh, M.R. The early Cretaceous Mansourabad shale-carbonate hosted Zn–Pb (-Ag) deposit, central Iran: An example of vent-proximal sub-seafloor replacement SEDEX mineralization. Ore Geology Reviews 2018, 95, 20-39.
[14] Ghorbani, M. Lithostratigraphy of Iran; Springer: 2019.
[15] Ghorbani, M. Metallogenic and mining provinces, belts and zones of Iran. In The economic geology of Iran; Springer: 2013; pp. 199-295.
[16] Ghorbani, M. A summary of geology of Iran. In The economic geology of Iran; Springer: 2013; pp. 45-64.
[17] Shabani, A.; Ziaii, M.; shirazy, A.; shirazi, A. Multi-Dimensional Data Fusion for Mineral Prospectivity Mapping (MPM) Using Fuzzy-AHP Decision-Making Method, Kodegan-Basiran Region, East Iran. Minerals 2022, 12.
[18] Hamedani, G.; Ahsanullah, M. Characterizations of Weibull geometric distribution. Journal of Statistical Theory and Applications 2011, 10, 581-590.
[19] Xunde, H.; Dingyuan, Z. Geochemical zoning pattern of the Yinyan tin deposit. Journal of Geochemical Exploration 1989, 33, 109-119.
[20] Solovov, A.P.; Kuznetov, V. Geochemical prospecting for mineral deposits; Mir Publ.: 1987.
[21] Gonçalves, M.A.; Mateus, A.; Pinto, F.; Vieira, R. Using multifractal modelling, singularity mapping, and geochemical indexes for targeting buried mineralization: Application to the W-Sn Panasqueira ore-system, Portugal. Journal of Geochemical Exploration 2018, 189, 42-53.
[22] Cheng, Q.; Harris, J. GIS-based multifractal anomaly analysis for prediction of mineralization and mineral deposits. Development of GIS in Geosciences. Special volume of GAC/MAC 2006, 289-300.
[23] Xiao, F.; Chen, Z.; Chen, J.; Zhou, Y. A batch sliding window method for local singularity mapping and its application for geochemical anomaly identification. Computers & geosciences 2016, 90, 189-201.
[24] Ziaii, M.; Pouyan, A.A.; Ziaii, M. Geochemical anomaly recognition using fuzzy C-means cluster analysis. Wseas transactions on systems 2006, 5, 2424-2429.
[25] Solovov A. P. and Kuznetov V. (1987), "Geochemical prospecting for mineral deposits", Mir Publ
[26] Berman, J.J. Data simplification: taming information with open source tools; Morgan Kaufmann: 2016.
[27] John, D.A.; Ayuso, R.; Barton, M.; Blakely, R.; Bodnar, R.; Dilles, J.; Gray, F.; Graybeal, F.; Mars, J.; McPhee, D. Porphyry copper deposit model. Chapter B of Mineral deposit models for resource assessment: US Geological Survey Scientific Investigations Report 2010, 169.
[28] Hezarkhani, A. Petrology of the intrusive rocks within the Sungun porphyry copper deposit, Azerbaijan, Iran. Journal of Asian Earth Sciences 2006, 27, 326-340.
[29] Zuo, R.; Xia, Q.; Zhang, D. A comparison study of the C–A and S–A models with singularity analysis to identify geochemical anomalies in covered areas. Applied geochemistry 2013, 33, 195-212.
[30] Saaty, R.W. The analytic hierarchy process—what it is and how it is used. Mathematical modelling 1987, 9, 161-176.
[31] Congalton, R.G. A review of assessing the accuracy of classifications of remotely sensed data. Remote sensing of environment 1991, 37, 35-46.
[32] Sochevanov, N.N. 1983: Selection of elements for calculation of the sequences of geochemical zoning in ore deposits Pages 166-168 1983
[33] Story, M.; Congalton, R.G. Accuracy assessment: a user’s perspective. Photogrammetric Engineering and remote sensing 1986, 52, 397-399.
[34] Lillesand, T.; Kiefer, R.; Chipman, J. Remote Sens $ ing and Image Interpretation. John Wiley & Sons Inc. New York 1994.
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