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A multi-disciplinary and exploratory geospatial data set integration for porphyry copper prospectivity mapping in Kerman belt, Iran | ||
| International Journal of Mining and Geo-Engineering | ||
| مقاله 4، دوره 57، شماره 4، اسفند 2023، صفحه 381-387 اصل مقاله (1 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/ijmge.2023.355306.595036 | ||
| نویسندگان | ||
| Sareh Sadigh1؛ Mirsaleh Mirmohammadi* 1؛ Omid Asghari1؛ Alok Porwal2 | ||
| 1School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran. | ||
| 2Centre for Studies in Resources Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, Maharashtra, India | ||
| چکیده | ||
| The Mineral Prospectivity Map (MPM) is a powerful tool for identifying target areas for the exploration of undiscovered mineral deposits. In this study, a knowledge-driven Index overlay technique was utilized to create the MPM on a regional scale. The complex distribution patterns of geological features associated with mineral deposits were mapped and correlations between these features and mineral deposits were revealed by integrating geological, geophysical, hydrothermal alteration, and fault density data layers. It was found that 23% of the study area was highly prospective, with 77% of the known porphyry copper occurrences located within this area. The normalized density was equal to 3.35, indicating a significant relationship between the known porphyry copper occurrences and their occupied area. The MPM also identified potential tracts outside the known mineralized areas that can be used for exploration and quantitative assessment of undiscovered resources. It is suggested that the MPM is a valuable tool for mineral exploration and could have significant implications for the mining industry. | ||
| کلیدواژهها | ||
| Index overlay؛ Kerman Cenozoic Magmatic Belt؛ Mineral prospectivity map؛ Porphyry copper deposit؛ Prediction-area (P-A) plot | ||
| مراجع | ||
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[1] E. J. M. Carranza and A. G. Laborte, “Data-driven predictive mapping of gold prospectivity, Baguio district, Philippines: Application of Random Forests algorithm,” Ore Geol. Rev., vol. 71, pp. 777–787, 2015.
[2] M. Yousefi and E. J. M. Carranza, “Geometric average of spatial evidence data layers: a GIS-based multi-criteria decision-making approach to mineral prospectivity mapping,” Comput. Geosci., vol. 83, pp. 72–79, 2015.
[3] A. Porwal, E. J. M. Carranza, and M. Hale, “Artificial neural networks for mineral-potential mapping: a case study from Aravalli Province, Western India,” Nat. Resour. Res., vol. 12, no. 3, pp. 155–171, 2003.
[4] M. Abedi, G.-H. Norouzi, and N. Fathianpour, “Fuzzy outranking approach: a knowledge-driven method for mineral prospectivity mapping,” Int. J. Appl. Earth Obs. Geoinf., vol. 21, pp. 556–567, 2013.
[5] M. Abedi, S. A. Torabi, G.-H. Norouzi, and M. Hamzeh, “ELECTRE III: A knowledge-driven method for integration of geophysical data with geological and geochemical data in mineral prospectivity mapping,” J. Appl. Geophys., vol. 87, pp. 9–18, 2012.
[6] M. Abedi, S. B. M. Kashani, G.-H. Norouzi, and M. Yousefi, “A deposit scale mineral prospectivity analysis: A comparison of various knowledge-driven approaches for porphyry copper targeting in Seridune, Iran,” J. African Earth Sci., vol. 128, pp. 127–146, 2017.
[7] M. Shabankareh and A. Hezarkhani, “Application of support vector machines for copper potential mapping in Kerman region, Iran,” J. African Earth Sci., vol. 128, pp. 116–126, 2017.
[8] S. Ghasemzadeh, A. Maghsoudi, M. Yousefi, and M. J. Mihalasky, “Stream sediment geochemical data analysis for district-scale mineral exploration targeting: Measuring the performance of the spatial U-statistic and CA fractal modeling,” Ore Geol. Rev., vol. 113, p. 103115, 2019.
[9] H. Rahimi, M. Abedi, M. Yousefi, A. Bahroudi, and G. R. Elyasi, “Supervised mineral exploration targeting and the challenges with the selection of deposit and non-deposit sites thereof,” Appl. Geochemistry, vol. 128, no. December 2020, p. 104940, 2021.
[10] G. F. Bonham-Carter, “Geographic information systems for geoscientists-modeling with GIS,” Comput. methods Geosci., vol. 13, p. 398, 1994.
[11] L. Zürcher et al., “Porphyry copper assessment of the Tethys region of western and southern Asia: Chapter V in Global mineral resource assessment,” US Geological Survey, 2015.
[12] J. D. Lowell and J. M. Gumbert, “Lateral and vertical alteration-mineralization zoning in porphyry ore deposits: Econ,” in Geol, 1970.
[13] R. H. Sillitoe, “Porphyry copper systems,” Econ. Geol., vol. 105, no. 1, pp. 3–41, Jan. 2010.
[14] A. P. Crosta, C. R. De Souza Filho, F. Azevedo, and C. Brodie, “Targeting key alteration minerals in epithermal deposits in Patagonia, Argentina, using ASTER imagery and principal component analysis,” Int. J. Remote Sens., vol. 24, no. 21, pp. 4233–4240, 2003.
[15] F. A. Kruse et al., “The spectral image processing system (SIPS)—interactive visualization and analysis of imaging spectrometer data,” Remote Sens. Environ., vol. 44, no. 2–3, pp. 145–163, 1993.
[16] G. I. Tripp, “Nature of the Archaean zuleika shear zone, Kalgoorlie, Western Australia,” in Applied Structural Geology for Mineral Exploration and Mining, Kalgoorlie 2002, Australian Institute of Geoscientists, Extended Abstracts, 2002, pp. 212–215.
[17] G. I. Tripp, “Fault control on Archaean gold deposits, Ora Banda, Western Australia,” Aust. Inst. Geosci. Newsl., vol. 62, pp. 1–6, 2000.
[18] R. H. Sibson, “Earthquake rupturing as a mineralizing agent in hydrothermal systems.,” Geology, vol. 15, no. 8, pp. 701–704, Aug. 1987.
[19] D. P. Cox, “Descriptive model of porphyry Cu,” Miner. Depos. Model. US Geol. Surv. Bull., vol. 1693, p. 76, 1986.
[20] R. M. Tosdal, “Magmatic and structural controls on the development of porphyry Cu±Mo±Au deposits,” Rev. Econ. Geol., vol. 14, pp. 157–181, 2001.
[21] H. O. Safari, L. Bagas, and B. Shafiei Bafti, “Structural controls on the localization of Cu deposits in the Kerman Cu metallogenic province of Iran using geoinformatic techniques,” Ore Geol. Rev., vol. 67, pp. 43–56, 2015.
[22] E. J. M. Carranza, Geochemical anomaly and mineral prospectivity mapping in GIS, vol. 11. Elsevier, 2008.
[23] A. Porwal, E. J. M. Carranza, and M. Hale, “Knowledge-driven and data-driven fuzzy models for predictive mineral potential mapping,” Nat. Resour. Res., vol. 12, no. 1, pp. 1–25, 2003.
[24] A. Porwal, E. J. M. Carranza, and M. Hale, “A hybrid neuro-fuzzy model for mineral potential mapping,” Math. Geol., vol. 36, no. 7, pp. 803–826, 2004.
[25] A. Porwal, E. J. M. Carranza, and M. Hale, “A hybrid fuzzy weights-of-evidence model for mineral potential mapping,” Nat. Resour. Res., vol. 15, no. 1, pp. 1–14, 2006.
[26] M. Yousefi, A. Kamkar-Rouhani, and E. J. M. Carranza, “Geochemical mineralization probability index (GMPI): a new approach to generate enhanced stream sediment geochemical evidential map for increasing probability of success in mineral potential mapping,” J. Geochemical Explor., vol. 115, pp. 24–35, 2012.
[27] M. Yousefi and E. J. M. Carranza, “Fuzzification of continuous-value spatial evidence for mineral prospectivity mapping,” Comput. Geosci., vol. 74, pp. 97–109, 2015.
[28] M. Yousefi, E. J. M. Carranza, and A. Kamkar-Rouhani, “Weighted drainage catchment basin mapping of stream sediment geochemical anomalies for mineral potential mapping,” J. Geochemical Explor., vol. 128, pp. 88–96, 2013.
[29] M. Yousefi and E. J. M. Carranza, “Data-driven index overlay and Boolean logic mineral prospectivity modeling in greenfields exploration,” Nat. Resour. Res., vol. 25, no. 1, pp. 3–18, 2016.
[30] M. J. Mihalasky and G. F. Bonham-Carter, “Lithodiversity and its spatial association with metallic mineral sites, Great Basin of Nevada,” Nat. Resour. Res., vol. 10, no. 3, pp. 209–226, 2001.
[31] M. Yousefi and J. M. A. Hronsky, “Translation of the function of hydrothermal mineralization-related focused fluid flux into a mappable exploration criterion for mineral exploration targeting,” Appl. Geochemistry, vol. 149, no. January, p. 105561, 2023.
[32] G. Last and M. Holtmann, “1 Introduction 2 Some general facts.”
[33] S. J. Yousefia, H. Ranjbar, S. Alirezaeics, S. Dargahid, and D. R. Lentze, “Comparison of Hydrothermal Alteration Patterns Associated with Porphyry Cu Deposits hosted by Granitoids and Intermediate-mafic Volcanic rocks, Kerman Magmatic Arc, Iran: application of geological, mineralogical and remote sensing data,” J. African Earth Sci., vol. 142, pp. 112–123, 2018.
[34] M. D. Dimitrijevic and I. Djokovic, Geological Map of Kerman Region. Institute for geological and mining exploration and investigation of nuclear and other mineral raw materials, 1973.We thank professor Maysam Abedi for his guidance and help in keeping our development on track, and professor Alok Porwal for comments that greatly improved the manuscript. | ||
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