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Investigation of copper and gold prospects using index overlay integration method and multifractal modeling in Saveh 1:100,000 sheet, Central Iran

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PL
Perspektywy poszukiwań miedzi i złota metodą wskaźnika integracji i modelowania multifraktalnego w Saveh, skala 1:100 000, Centralny Iran
Języki publikacji
EN
Abstrakty
EN
This study aims at prospecting copper and gold promising areas in Saveh 1:100,000 sheet, situated in Urumieh-Dokhtar magmatic belt (Central Iran). Geographic information system (GIS) is effective in recognition of probable mineral resources by collecting, processing, exploration layer weighting and integrating thematic maps. As there is no certainty in different geological phenomena, modeling and integrating information layers are used to obtain suitable results for determining potential areas. In this study, index overlay method, which is a combination of software processing and expertise knowledge, was used. The survey layers consist of the lithologic units, geophysical data, mineralization, faults and structures and alteration. [...]
PL
Badanie to ma na celu poszukiwanie miedzi i złota z perspektywicznych obszarów w Saveh na arkuszu 1:100 000, położonego w pasie magmowym w Urumieh-Dokhtar (Centralny Iran). System informacji geograficznej (GIS) jest skuteczny w rozpoznaniu przypuszczalnych zasobów surowców mineralnych poprzez gromadzenie, przetwarzanie warstwy ważenia poszukiwań i integracji map tematycznych. W celu uzyskania właściwych wyników dla potrzeb określenia potencjalnych obszarów do eksploatacji, użyto techniki modelowania i zintegrowanej informacji o warstwach geologicznych. W tym badaniu została użyta metoda wskaźnikowa, która jest kombinacją komputerowego sposobu przetwarzania danych i wiedzy eksperckiej. Badane warstwy geologiczne opisane są pojęciami litologicznymi, danymi geofizycznymi, stopniem mineralizacji oraz zaburzeniami tektonicznymi. [...]
Twórcy
autor
  • Department of Geology, North Tehran Branch, Islamic Azad University, Tehran, Iran
autor
  • Department of Geology, North Tehran Branch, Islamic Azad University, Tehran, Iran
autor
  • Department of Mining Engineering, South Tehran Branch, Faculty of Engineering, Islamic Azad University, Tehran, Iran; Camborne School of Mines, University of Exeter, Penryn, UK
autor
  • Department of Geology, North Tehran Branch, Islamic Azad University, Tehran, Iran
  • Department of Geology, Science and Research Branch, Islamic Azad University, Tehran, Iran
  • Department of Geology, Science and Research Branch, Islamic Azad University, Tehran, Iran
Bibliografia
  • [1] Afzal et al. 2010 – Afzal, P., Khakzad, A., Moarefvand, P., Rashidnejad Omran, N., Esfandiari, B. and Fadakar Alghalandis, Y. 2010. Geochemical anomaly separation by multifractal modeling in Kahang (GorGor) porphyry system. Central Iran. Journal of Geochemical Exploration 104, pp. 34–46.
  • [2] Afzal et al. 2012 – Afzal, P., Fadakar Alghalandis, Y., Moarefvand, P., Rashidnejad Omran, N. and Asadi Haroni, H. 2012. Application of power-spectrum-volume fractal method for detecting hypogene, supergene enrichment, leached and barren zones in Kahang Cu porphyry deposit, Central Iran. Journal of Geochemical Exploration 112, pp. 131–138.
  • [3] Afzal et al. 2013 – Afzal, P., Dadashzadeh Ahari, H., Rashidnejad Omran, N. and Aliyari, F. 2013. Delineation of gold mineralized zones using concentration–volume fractal model in Qolqoleh gold deposit, NW Iran. Ore Geology Review 55, pp. 125–133.
  • [4] Afzal et al. 2014 – Afzal, P., Alhoseini, S.H., Tokhmechi, B., Kaveh Ahangaran, D., Yasrebi, A.B., Madani, N. and Wetherelt, A. 2014. Outlining of high quality coking coal by concentration–volume fractal model and turning bands simulation in East-Parvadeh coal deposit, Central Iran. International Journal of Coal Geology 127, pp. 88–99.
  • [5] Agterberg, F.P. 1995. Multifractal modeling of the sizes and grades of giant and supergiant deposits. International Geology Review 37, pp. 1–8.
  • [6] Almasi et al. 2014 – Almasi, A., Jafarirad, A., Kheyrollahi, H., Rahimi, M. and Afzal, P. 2014. Evaluation of structural and geological factors in orogenic gold type mineralization using airborne geophysical data, Kervian area, NW of Iran. Exploration Geophysicists doi:10.1071/EG13053.
  • [7] Berberian, M. and King, G.C. 1981. Towards a paleogeography and tectonic evolution of Iran. Canadian Journal of Earth Sciences 18, pp. 210–265.
  • [8] Bonham-Carter, G.F. 1991. Geographic Information System for Geoscientists: Modeling with GIS. Ontario: Pergamon press, 470 pp.
  • [9] Bonham-Carter, G.F. 1994. Geographic Information Systems for Geoscientists: Modelling with GIS. Oxford: Pergamon Press, 398 pp.
  • [10] Bonnefoy et al. 2002 – Bonnefoy, D., Braux, C., Corpel, G., Delpont, G. and Weber, C. 2002. Combined interpretation of remote sensing imagery and geophysical data: exploration for gold in southern Brittany, France. Advances in Space Research 12(7), pp. 17-25.
  • [11] Carranza et al. 1999 – Carranza, E.J.M., Mangaoang, J.C. and Haleh, M. 1999. Application of mineral exploration models and GIS to generate mineral potential maps as input for optimum land-use planning in the Philippines. Natural Resources Research 2(8), pp. 165–173.
  • [12] Carranza, E.J.M. 2002. Geologically-constrained mineral potential mapping. Ph.D thesis, ITC Delft, Netherlands, pp. 1–474.
  • [13] Carranza, E.J.M. 2008. Geochemical anomaly and mineral prospectivity mapping in GIS. Amsterdam: Elsevier, 368 pp.
  • [14] Cassard et al. 2008 – Cassard, C., Billa, M., Lambert, A., Picot, J., Husson, Y., Lasserre, L. and Delor, C. 2008. Gold predictivity mapping in French Guiana using an expert-guided data-driven approach based on a regional-scale GIS. Ore Geology Reviews 34, pp. 471–500.
  • [15] Cheng et al. 1994 – Cheng, Q., Agterberg, F.P.and Ballantyne, S.B. 1994. The separation of geochemical anomalies from background by fractal methods. Journal of Geochemical Exploration 51, pp. 109–130.
  • [16] Cheng, Q. 1999. Spatial and scaling modelling for geochemical anomaly separation. Journal of Geochemical Exploration 65(3), pp. 175–194.
  • [17] Cheng, Q. and Agterberg, F.P. 2009. Singularity analysis of ore-mineral and toxic trace elements in stream sediments. Computers & Geosciences 35(2), pp. 234–244.
  • [18] Chico-Olmo et al. 2002 – Chico-Olmo, M., Abarca, F. and Rigol, J.P. 2002. Development of a decision support system based on remote sensing and GIS techniques for gold-rich area identification in SE Spain. International Journal of Remote Sensing 232, pp. 4801–4814.
  • [19] Dargahi et al. 2010 – Dargahi, S., Arvin, M., Pan, Y. and Babaei, A. 2010. Petrogenesis of Post-Collisional A-type granitoid from the Urumieh-Dokhtar magmatic assemblage, Southwestern Kerman, Iran: constraints on the Arabian-Eurasian continental collision. Lithos 115, pp. 190–204.
  • [20] Davis J.C. 2002. Statistics and data analysis in Geology. New York: John Wiley and Sons Inc, 638 pp.
  • [21] Feltrin, L. 2008. Predictive modeling of prospectivity for Pb–Zn deposits in the Lawn Hill Region, Queensland, Australia. Ore Geology Reviews 34, pp. 399–427.
  • [22] Filho et al. 2007 – Filho, C.R.S., Nunes, A.R., Leite, E.P., Monteiro, L.V.S. and Xavier, R.P. 2007. Spatial Analysis of Airborne Geophysical Data Applied to Geological Mapping and Mineral Prospecting in the Serra Leste Region, Caraja´s Mineral Province, Brazil. Surveys in Geophysics 28, pp. 377–405.
  • [23] Ghalamghash et al. 1998 – Ghalamghash, J., Fonoudi, M. and Mehrpartou, M. eds. 1998. Geological map of Saveh 1:100,000 sheet. Tehran: Geological Survey of Iran.
  • [24] Hariri, M. 2003. Use of GIS (geographic information system) in determining relationship between geology, structure and mineral prospects, southern part of the Arabian Shield, Saudi Arabia, Pakistan. Journal of Applied Sciences 3(2), pp. 92–96.
  • [25] Harris, J.R. 1989. Data integration for gold exploration in eastern Nova Scotia using a GIS. Remote Sensing for Exploration Geology. Calgary, Alberta, pp. 233–249.
  • [26] Hosseinali, F. and Alesheikh, A. 2008. Weighting Spatial Information in GIS for Copper Mining Exploration. American Journal of Applied Sciences pp. 1187–1198.
  • [27] Karimi, M. and Valadan Zoej, M.J. 2004. Mineral potential mapping of copper minerals with GIS. Geo-Imagery Bridging Continents, XXth ISPRS Congress. Istanbul, 12-23 July, 2004. pp. 1103–1108.
  • [28] Li et al. 2003 – Li, C.J., Ma, T.H. and Shi, J.F. 2003. Application of a fractal method relating concentration and distances for separation of geochemical anomalie from background. Journal of Geochemical Exploration 77, pp. 167–175.
  • [29] Malczewski, J. 2006. Ordered weighted averaging with fuzzy quantifiers: GIS-based multicriteria evaluation for land-use suitability analysis. International Journal of Applied Earth Observation and Geo information 8(4), pp. 270–277.
  • [30] Mandelbrot, B.B. 1983. The fractal geometry of Nature. San Fransisco: W.H. Freeman, 468 pp.
  • [31] Moradi et al. 2014 – Moradi, M., Basiri, S., Kananian, A. and Kabiri, K. 2014. Fuzzy logic modeling for hydrothermal gold mineralization mapping using geochemical, geological, ASTER imageries and other geo-data, a case study in Central Alborz, Iran. Earth science informatics doi:10.1007/s12145-014-0151-9.
  • [32] Noorollahi et al. 2008 – Noorollahi,Y., Itoi, R., Fujii, H. and Tanaka, T. 2008. GIS integration model for geothermal exploration and well siting. Geothermics 37, pp.107–131.
  • [33] Partington, G. 2010. Developing models using GIS to assess geological and economic risk: an example from VMS copper gold mineral exploration in Oman. Ore Geology Reviews 38, pp. 197–207.
  • [34] Pazand et al. 2011 – Pazand, K., Hezarkhani, A., Ataei, M. and Ghanbari, Y. 2011. Combining AHP with GIS for predictive Cu porphyry potential mapping: a case study in Ahar Area (NW, Iran). Natural Resources Research 20(4), pp. 251–262.
  • [35] Pazand et al. 2014 – Pazand, K., Hezarkhani, A. and Ghanbari, Y. 2014. Fuzzy analytical hierarchy process and GIS for predictive Cu porphyry potential mapping: a case study in Ahar–Arasbaran Zone (NW, Iran). Arabian Journal of Geosciences 7, pp. 241–251.
  • [36] Porwal et al. 2003 – Porwal, A., Carranza, E. and Hale, M. 2003. Knowledge-driven and Data-driven Fuzzy Models for Predictive Mineral Potential Mapping. Natural Resources Research 12(1), pp. 1–25.
  • [37] Porwal et al. 2006 – Porwal, A., Carranza, E.J.M. and Hale, M. 2006. A Hybrid Fuzzy Weights-of-Evidence Model for Mineral Potential Mapping. Natural Resources Research 15, pp. 1–14.
  • [38] Rezaei Kahkhaei et al. 2011 – Rezaei Kahkhaei, M., Galindo, C., Pankhurst, R.J. and Esmaeily, D. 2011. Magmatic differentiation in the calc-alkaline Khalkhab–Neshveh pluton, Central Iran. Journal of Asian Earth Sciences 42, pp. 499–514.
  • [39] Saeedi et al. 2013 – Saeedi, A., Maqsoudi, A. and Younesi, S. eds. 2013. Geochemical Exploration in Saveh 1:100,000 Sheet. Tehran: Geological Survey of Iran, 187 pp. (in Persian).
  • [40] Shahabpour, J. 1994. Post-mineral brecciadyke from the Sar-Cheshmehporphyry copper deposit, Kerman, Iran. Exploration and Mining Geology Journal 3, pp. 39–43.
  • [41] Shamseddin Meigoony et al. 2014 – Shamseddin Meigoony, M., Afzal, P., Gholinejad, M., Yasrebi, A.B. and Sadeghi, B. 2014. Delineation of geochemical anomalies using factor analysis and multifractal modeling based on stream sediments data in Sarajeh 1:100,000 sheet, Central Iran. Arabian Journal of Geosciences 7, pp. 5333–5343.
  • [42] Silva et al. 2003 – Silva, A.M., Pires, A.C. and McCaffery, A. 2003. Application of airborne geophysical data to mineral exploration in the uneven exposed terrains of the Rio Das Velhas greenstone belt. Revista Brasileira de Geociencias 33, pp. 17–28.
  • [43] Sim et al. 1999 – Sim, B.L., Agterberg, F.P. and Beaudry, C. 1999. Determining the cutoff between background and relative base metal contamination levels using multifractal methods. Computers & Geosciences 25, pp. 1023–1041.
  • [44] Yousefifar et al. 2011 – Yousefifar, S., Khakzad, A., Asadi Harooni,H., Karami, J., Jafari, M.R. and Vosoughi Abedin, M. 2011. Prospecting of Au and Cu bearing targets by exploration data combination in southern part of dalli Cu-Au porphyry deposit, central iran. Archives of Mining Sciences 56(1), pp. 21–34.
  • [45] Zuo, R. 2011. Identifying geochemical anomalies associated with Cu and Pb–Zn skarn mineralization using principal component analysis and spectrum–area fractal modeling in the Gangdese Belt, Tibet (China). Journal of Geochemical Exploration 111, pp. 13–22.
  • [46] Zuo et al. 2009 – Zuo, R., Cheng, Q. and Xia, Q. 2009. Application of fractal models to characterization of vertical distribution of geochemical element concentration. Journal of Geochemical Exploration 102(1), pp. 37–43.
  • [47] Zuo et al. 2013 – Zuo, R., Xia, Q. and Zhang,D.A. 2013. comparison study of the C–A and S–A models with singularity analysis to identify geochemical anomalies in covered areas. Applied Geochemistry 33, pp. 165–172.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-7097f04d-758c-457d-a860-0c309e91616d
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