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Integration and analysis of geological, geochemical and remote sensing data of south of Neyshabur using principal component analysis | ||
| International Journal of Mining and Geo-Engineering | ||
| دوره 55، شماره 2، اسفند 2021، صفحه 161-170 اصل مقاله (1.28 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/ijmge.2020.292411.594830 | ||
| نویسندگان | ||
| Hamed Fazliani* ؛ Abolghasem Kamkar-Rouhani؛ Alireza Arab-Amiri | ||
| Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran | ||
| چکیده | ||
| Lack of the existence of known mineral prospects in the preliminary stages of mineral exploration is the main problem of data-driven mineral potential modeling methods. On the other hand, applying the expert’s knowledge and judgment in different stages of mineral potential modeling, is the main difficulty of knowledge-driven mineral potential modeling methods. In addition, other difficulties in these methods can be mentioned such as determination of important variables, weighting to various classes of maps or information layers, and so on. Hence, the accuracy of the results of the knowledge-driven modeling methods is highly dependent on the amount of knowledge and experience of the expert. In this study, the principal component analysis (PCA) has been introduced as a knowledge-driven method with the least reliance on the expert’s knowledge for mineral potential modeling. In this method, the expert’s knowledge is only used in the interpretation of the results obtained from the modeling, and is not considered in the first stages of mineral potential modeling and definition of the conceptual model. In the introduced method, the interpretation of the results is conducted based on the positive and negative coefficients of variables in the eigenvalues table. Using these coefficients, it is determined that each principal component (PC) is associated with what type of mineralization. An advantage of this introduced method is to identify various types of mineralization in the area of interest using just one modeling effort. In order to evaluate the efficiency of this method, a region including two geological maps of Kadkan and Shamkan in the south of Neyshabur, northeast of Iran was selected. Two mineralization types including podiform chromite and epithermal gold-antimony mineralization types have been identified using the proposed method that presents more precise results than those of conventional univariate and multivariate geochemical studies. | ||
| کلیدواژهها | ||
| Mineral potential modeling؛ Principal component analysis؛ Podiform chromite deposit؛ Epithermal gold deposit؛ Kadkan and Shamkan area | ||
| مراجع | ||
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[1] Yang, J., Cheng, Q. (2015 a). A comparative study of independent component analysis with principal component analysis in geological objects identification, Part I: Simulations. Journal of Geochemical Exploration, 149, 127–135.
[2] Davis, J. C. (2002). Statistics and Data Analysis in Geology. 3rd ed, JohnWiley & SonsInc, New York.
[3] Cheng, Q., Bonham-Carter, G., Wang, W., Zhang, S., Li, W., Xia, Q. (2011). A spatially weighted principal component analysis for multi-element geochemical data for mapping locations of felsic intrusions in the Gejiu mineral district of Yunnan, China. Computers & Geosciences, 37 (5), 662–669.
[4] Wang, W., Zhao, J., Cheng, Q. (2011). Analysis and integration of geo-information to identify granitic intrusions as exploration targets in southeastern Yunnan District, China. Computers & Geosciences, 37, 1946–1957.
[5] 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, 13–22.
[6] Yang, J., Cheng, Q. (2015 b). A comparative study of independent component analysis with principal component analysis in geological objects identification, Part II: A case study of Pinghe District, Fujian, China, Journal of Geochemical Exploration, 149, 136–146.
[7] Ueki, K., and Iwamori, H. (2017). Geochemical differentiation processes for arc magma of the Sengan volcanic cluster, Northeastern Japan, constrained from the principal component analysis. Lithos, 290, 60–75.
[8] Davydenko, A. Y., Grayver, A. V. (2014). Principal component analysis for filtering and leveling of geophysical data. Journal of Applied Geophysics, 109, 266–280.
[9] Li, Q., Dehler, S. A. (2015). Inverse spatial principal component analysis for geophysical survey data interpolation. Journal of Applied Geophysics, 115, 79-91.
[10] Wang, J., Xiaohong, M., Li, F. (2015). Improved curvature gravity gradient tensor with principal component analysis and its application in edge detection of gravity data. Journal of Applied Geophysics, 118, 106–114.
[11] Zhang, Q., Peng, C., Lu, Y., Wang, H., Zhu, K. (2018). Airborne electromagnetic data levelling using principal component analysis based on flight line difference. Journal of Applied Geophysics, 151, 290–297.
[12] Ghosh, T., Basu S., Hazra S. (2014). Geological mapping of the Schuppen belt of north-east India using geospatial technology. Journal of Asian Earth Sciences, 79, 97–111.
[13] Mandeng, E. P. B., Bidjeck, L. M. B., Wambo, J. D. T., Taku, A., Betsi, T. B., Ipan, A. S., Nfada, L. T., Dieudonné, L. B. (2018). Lithologic and structural mapping of the Abiete–Toko gold district in southern Cameroon, using Landsat 7 ETM+/SRTM. Comptes Rendus Geoscience, 350, 130–140.
[14] Fazliani, H., Kamkar-Rouhani, A., Arab-Amiri, A. R. (2019). Fuzzy logic and principal component analysis for mineral potential modeling of epithermal gold-antimony deposits in southern Neyshabur. 11th Symposium of the Iranian Society of Economic Geology. Ahvaz, Iran.
[15] Ranjbar, H., Hassanzadeh, H., Torabi, M., Ilaghi, O. (2001). Integration and analysis of airborne geophysical data of the Darrehzar area, Kerman Province, Iran, using principal component analysis. Journal of applied geophysics , 48, 33–41.
[16] Honarmand, M., Ranjbar, H., Moezifar, Z. (2002). Integration and analysis of airborne geophysics and remote sensing data of sar-cheshmeh area, using directed principal component analysis. Exploration and Mining Geology, 11, 43–48.
[17] Ranjbar, H., Honarmand, M., Moezifar, Z. (2003b). Integration and analysis of airborne geophysics and remote sensing data for exploration of porphyry copper deposits in the Central Iranian Volcanic Belt. Map Asia Conference.
[18] Dezhong, H., Delian, L., Shuigen, X. (1995a). Explanatory text of geochemical map of Shamkan, stream sediment survey. Geological Survey of Iran Press
[19] Naderi Mighan, N. (1998). Geological map of Shamkan (1:100000). Geological Survey of Iran Press.
[20] Naderi Mighan, N. (1999). Geological map of Kadkan (1:100000) . Geological Survey of Iran Press.
[21] Carranza, E. J. M., (2008). Geochemical anomaly and mineral prospectivity mapping in GIS, handbook of exploration and environmental geochemistry. Vol. 11, Elsevier, Amsterdam.
[22] Rencher, A. C. (2002). Method of Multivariate Analysis . second Edition, Wiley series in probability and statistics.
[23] Sabins, F. F. (1999). Remote sensing for mineral exploration. Remote Sensing Enterprises, 1724 Celeste Lane, Fullerton, CA 92833, USA, 157–183.
[24] Ranjbar, H., Honarmand, M., Moezifar, Z. (2003a). Analysis of ETM+ and airborne geophysical data for exploration of porphyry type deposits in the Central Iranian Volcanic Belt, using fuzzy classification. Remote sensing for environmental monitoring, GIS applications, and geology III. SPIE Conference, Barcelona, Spain.
[25] Stern, R. J. (1999). Mineral exploration with satellite remote sensing imagery: examples from the Neoproterozoic Arabian-Nubian Shield. 11th International Conference of the Geological Society of Africa.
[26] Volesky, J. C., Stern, R. J., Johnson, P. R. (2003). Geological control of massive sulfide mineralization in the Neoproterozoic Wadi Bidah shear zone, southwestern Saudi Arabia, inferences from orbital remote sensing and field studies. Precambrian Research, 123, 235–247.
[27] Adler-Golden, S., Berk, A., Bernstein, L. S., Richtsmeier, S., Acharya, P. K., Matthew, M. W., Anderson, G. P., Allred, C., Jeong, L. Chetwynd, J. H. (1998). FLAASH, a MODTRAN4 atmospheric correction package for hyperspectral data retrievals and simulations. In Summaries of the seventh JPL airborne earth science workshop. 9-14.
[28] Costa, L., Nunes, L., Ampatzidis, Y. (2020). A new visible band index (vNDVI) for estimating NDVI values on RGB images utilizing genetic algorithms. Computers and Electronics in Agriculture, 172.
[29] Hardcastle, K. C. (1995). Photolineament Factor: A new computer-aided method for remotely sensing the degree to which bedrock is fractured. Photogrammetric Engineering & Remote Sensing, 61(6), 739– 747.
[30] Dezhong, H., Delian, L., Shuigen, X. (1995b). Explanatory text of geochemical map of Kadkan, stream sediment survey. Geological Survey of Iran Press.
[31] Beus, A. A., Gregorian, S. V. (1975). Geochemical exploration methods for mineral deposits. Applied Pub. Ud., Wilmette. [32] Filzmoser P., Hron K., Reimann C. (2009). Principal component analysis for compositional data with outliers. Environmetrics, 20, 621–632.
[33] Salomão, G. N., Figueiredo, M. A., Dall'Agnol, R., Sahoo, P. K., de Medeiros Filho, C. A., da Costa, M. F., Angélica, R. S. (2019). Geochemical mapping and background concentrations of iron and potentially toxic elements in active stream sediments from Carajás, Brazil – implication for risk assessment. Journal of South American Earth Sciences, 92, 151–166.
[34] Bishop, M. (1996). Neural Networks for Pattern Recognition. MIT Press.
[35] Theodoridis, S., Koutroumbas, K. (1999). Pattern Recognition, Academic Press.
[36] Dorri, M. B., Sadeghi, Kh. (2008). Regional exploration on the Kadkan 1:100000 geological map. Geological Survey of Iran Press.
[37] Heydari, E., Manaf Nejad, M. S. (2009). Regional exploration on the Shamkan 1:100000 geological map. Geological Survey of Iran Press.
[38] Azmi, H. (2011). Mineral prospecting over an area of 500 km2 in different locations of Khorasan Razavi province. Geological Survey of Iran Press.
[39] Mosier, D. L., Singer, D. A., Moring, B. C., Galloway, J. P. (2012). Podiform chromite deposits database and grade and tonnage models, U.S. Geological Survey Scientific Investigations Report 2012–5157, 45 p. and database.
[40] Constantinou, G. (1980). Metallogenesis associated with Troodos ophiolite. In Panayiotou, A. (Ed.), Ophiolites. Proceedings of the International Ophiolite Symposium, Nicosia, Cyprus, 663–674.
[41] Yaghubpur, A. and Hassan Nejad A. A. (2006). The spatial distribution of some chromite deposits in Iran, Using Fry Analysis. Journal of Sciences, Islamic Republic of Iran, 17(2), 147–152.
[42] Wells, F. G., Cater, F. W., Jr., Rynearson, G. A. (1946). Chromite deposits of Del Norte County, California. California Division of Mines Bulletin, 134, 1–76.
[43] Abrams, M. J., Rothery, D. A., Pontual, A. (1988). Mapping in the Oman Ophiolite using enhanced Landsat Thematic Mapper images. Tectonophysics, 151, 387–401.
[44] Lipin, B. R. (1984). Chromite from the Blue Ridge Province of North Carolina. American Journal of Science, 284, 507–529.
[45] Fazliani, H., Rahimi Pour, Gh. R., Ranjbar, H. (2007). Investigation of mineral zoning in the Kadkan and Shamkan geological sheets using the stream sediment geochemical data. 26th Geoscience Conference. Geological Survey of Iran, Tehran.
[46] Hedenquist, J. W., Izawa, E., Arribas, A., White, N. C. (1996). Epithermal Gold Deposits: Styles, Characteristics, and Exploration. Society of Resource Geology of Japan.
[47] Simmons, S. F., White, N. C., JOHN, D. A. (2005). Geological Characteristics of Epithermal Precious and Base Metal Deposits: in: Hedenquist, J. W., Thompson, J. F. H., Goldfarb, R. J., and Richards, J. P., eds., Economic Geology 100th Anniversary Volume: The Economic Geology Publishing Company, 485–522
[48] Taylor, B. E. (2007). Epithermal gold deposits . in Goodfellow, W. D., ed., Mineral Deposits of Canada: A Synthesis of Major Deposit-Types, District Metallogeny, the Evolution of Geological Provinces, and Exploration Methods: Geological Association of Canada, Mineral Deposits Division, Special Publication No. 5, 113–139.
[49] Sawkins, F. J. (1990). Metal deposits in relation to plate tectonics. Berlin, Springer-Verlag, 461.
[50] Sillitoe, R. H., Hedenquist, J. W. (2003). Linkages between volcano-tectonic settings, ore fluid compositions, and epithermal precious metal deposits . Society of Economic Geologists Special Publication 10, 315–343.
[51] Bethke, P. M., Rye, R. O., Stoffregen, R. E., Vikre, P. G. (2005). Evolution of the magmatic-hydrothermal acid-sulfate system at Summitville, Colorado: Integration of geological, stable isotope, and fluid inclusion evidence. Chemical Geology, 215, 281–315.
[52] Arancibia, G., Matthews, S. J., Cornejo, P., Perez de Arce, C., Zuluaga, J. I., and Kasanevan, S. (2006). 40Ar/ 39Ar and K-Ar geochronology of magmatic and hydrothermal events in a classic low-sulphidation epithermal bonanza deposit; El Peñon, Northern Chile. Mineralium Deposita , 41, 505–516.
[53] Harvey, B., Myers, S., Klein, T. (1999). Yanacocha gold district, northern Peru. Pacific Rim Congress , Bali, Indonesia, Australasian Institute of M
[1] Yang, J., Cheng, Q. (2015 a). A comparative study of independent component analysis with principal component analysis in geological objects identification, Part I: Simulations. Journal of Geochemical Exploration, 149, 127–135.
[2] Davis, J. C. (2002). Statistics and Data Analysis in Geology. 3rd ed, JohnWiley & SonsInc, New York.
[3] Cheng, Q., Bonham-Carter, G., Wang, W., Zhang, S., Li, W., Xia, Q. (2011). A spatially weighted principal component analysis for multi-element geochemical data for mapping locations of felsic intrusions in the Gejiu mineral district of Yunnan, China. Computers & Geosciences, 37 (5), 662–669.
[4] Wang, W., Zhao, J., Cheng, Q. (2011). Analysis and integration of geo-information to identify granitic intrusions as exploration targets in southeastern Yunnan District, China. Computers & Geosciences, 37, 1946–1957.
[5] 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, 13–22.
[6] Yang, J., Cheng, Q. (2015 b). A comparative study of independent component analysis with principal component analysis in geological objects identification, Part II: A case study of Pinghe District, Fujian, China, Journal of Geochemical Exploration, 149, 136–146.
[7] Ueki, K., and Iwamori, H. (2017). Geochemical differentiation processes for arc magma of the Sengan volcanic cluster, Northeastern Japan, constrained from the principal component analysis. Lithos, 290, 60–75.
[8] Davydenko, A. Y., Grayver, A. V. (2014). Principal component analysis for filtering and leveling of geophysical data. Journal of Applied Geophysics, 109, 266–280.
[9] Li, Q., Dehler, S. A. (2015). Inverse spatial principal component analysis for geophysical survey data interpolation. Journal of Applied Geophysics, 115, 79-91.
[10] Wang, J., Xiaohong, M., Li, F. (2015). Improved curvature gravity gradient tensor with principal component analysis and its application in edge detection of gravity data. Journal of Applied Geophysics, 118, 106–114.
[11] Zhang, Q., Peng, C., Lu, Y., Wang, H., Zhu, K. (2018). Airborne electromagnetic data levelling using principal component analysis based on flight line difference. Journal of Applied Geophysics, 151, 290–297.
[12] Ghosh, T., Basu S., Hazra S. (2014). Geological mapping of the Schuppen belt of north-east India using geospatial technology. Journal of Asian Earth Sciences, 79, 97–111.
[13] Mandeng, E. P. B., Bidjeck, L. M. B., Wambo, J. D. T., Taku, A., Betsi, T. B., Ipan, A. S., Nfada, L. T., Dieudonné, L. B. (2018). Lithologic and structural mapping of the Abiete–Toko gold district in southern Cameroon, using Landsat 7 ETM+/SRTM. Comptes Rendus Geoscience, 350, 130–140.
[14] Fazliani, H., Kamkar-Rouhani, A., Arab-Amiri, A. R. (2019). Fuzzy logic and principal component analysis for mineral potential modeling of epithermal gold-antimony deposits in southern Neyshabur. 11th Symposium of the Iranian Society of Economic Geology. Ahvaz, Iran.
[15] Ranjbar, H., Hassanzadeh, H., Torabi, M., Ilaghi, O. (2001). Integration and analysis of airborne geophysical data of the Darrehzar area, Kerman Province, Iran, using principal component analysis. Journal of applied geophysics , 48, 33–41.
[16] Honarmand, M., Ranjbar, H., Moezifar, Z. (2002). Integration and analysis of airborne geophysics and remote sensing data of sar-cheshmeh area, using directed principal component analysis. Exploration and Mining Geology, 11, 43–48.
[17] Ranjbar, H., Honarmand, M., Moezifar, Z. (2003b). Integration and analysis of airborne geophysics and remote sensing data for exploration of porphyry copper deposits in the Central Iranian Volcanic Belt. Map Asia Conference.
[18] Dezhong, H., Delian, L., Shuigen, X. (1995a). Explanatory text of geochemical map of Shamkan, stream sediment survey. Geological Survey of Iran Press
[19] Naderi Mighan, N. (1998). Geological map of Shamkan (1:100000). Geological Survey of Iran Press.
[20] Naderi Mighan, N. (1999). Geological map of Kadkan (1:100000) . Geological Survey of Iran Press.
[21] Carranza, E. J. M., (2008). Geochemical anomaly and mineral prospectivity mapping in GIS, handbook of exploration and environmental geochemistry. Vol. 11, Elsevier, Amsterdam.
[22] Rencher, A. C. (2002). Method of Multivariate Analysis . second Edition, Wiley series in probability and statistics.
[23] Sabins, F. F. (1999). Remote sensing for mineral exploration. Remote Sensing Enterprises, 1724 Celeste Lane, Fullerton, CA 92833, USA, 157–183.
[24] Ranjbar, H., Honarmand, M., Moezifar, Z. (2003a). Analysis of ETM+ and airborne geophysical data for exploration of porphyry type deposits in the Central Iranian Volcanic Belt, using fuzzy classification. Remote sensing for environmental monitoring, GIS applications, and geology III. SPIE Conference, Barcelona, Spain.
[25] Stern, R. J. (1999). Mineral exploration with satellite remote sensing imagery: examples from the Neoproterozoic Arabian-Nubian Shield. 11th International Conference of the Geological Society of Africa.
[26] Volesky, J. C., Stern, R. J., Johnson, P. R. (2003). Geological control of massive sulfide mineralization in the Neoproterozoic Wadi Bidah shear zone, southwestern Saudi Arabia, inferences from orbital remote sensing and field studies. Precambrian Research, 123, 235–247.
[27] Adler-Golden, S., Berk, A., Bernstein, L. S., Richtsmeier, S., Acharya, P. K., Matthew, M. W., Anderson, G. P., Allred, C., Jeong, L. Chetwynd, J. H. (1998). FLAASH, a MODTRAN4 atmospheric correction package for hyperspectral data retrievals and simulations. In Summaries of the seventh JPL airborne earth science workshop. 9-14.
[28] Costa, L., Nunes, L., Ampatzidis, Y. (2020). A new visible band index (vNDVI) for estimating NDVI values on RGB images utilizing genetic algorithms. Computers and Electronics in Agriculture, 172.
[29] Hardcastle, K. C. (1995). Photolineament Factor: A new computer-aided method for remotely sensing the degree to which bedrock is fractured. Photogrammetric Engineering & Remote Sensing, 61(6), 739– 747.
[30] Dezhong, H., Delian, L., Shuigen, X. (1995b). Explanatory text of geochemical map of Kadkan, stream sediment survey. Geological Survey of Iran Press.
[31] Beus, A. A., Gregorian, S. V. (1975). Geochemical exploration methods for mineral deposits. Applied Pub. Ud., Wilmette. [32] Filzmoser P., Hron K., Reimann C. (2009). Principal component analysis for compositional data with outliers. Environmetrics, 20, 621–632.
[33] Salomão, G. N., Figueiredo, M. A., Dall'Agnol, R., Sahoo, P. K., de Medeiros Filho, C. A., da Costa, M. F., Angélica, R. S. (2019). Geochemical mapping and background concentrations of iron and potentially toxic elements in active stream sediments from Carajás, Brazil – implication for risk assessment. Journal of South American Earth Sciences, 92, 151–166.
[34] Bishop, M. (1996). Neural Networks for Pattern Recognition. MIT Press.
[35] Theodoridis, S., Koutroumbas, K. (1999). Pattern Recognition, Academic Press.
[36] Dorri, M. B., Sadeghi, Kh. (2008). Regional exploration on the Kadkan 1:100000 geological map. Geological Survey of Iran Press.
[37] Heydari, E., Manaf Nejad, M. S. (2009). Regional exploration on the Shamkan 1:100000 geological map. Geological Survey of Iran Press.
[38] Azmi, H. (2011). Mineral prospecting over an area of 500 km2 in different locations of Khorasan Razavi province. Geological Survey of Iran Press.
[39] Mosier, D. L., Singer, D. A., Moring, B. C., Galloway, J. P. (2012). Podiform chromite deposits database and grade and tonnage models, U.S. Geological Survey Scientific Investigations Report 2012–5157, 45 p. and database.
[40] Constantinou, G. (1980). Metallogenesis associated with Troodos ophiolite. In Panayiotou, A. (Ed.), Ophiolites. Proceedings of the International Ophiolite Symposium, Nicosia, Cyprus, 663–674.
[41] Yaghubpur, A. and Hassan Nejad A. A. (2006). The spatial distribution of some chromite deposits in Iran, Using Fry Analysis. Journal of Sciences, Islamic Republic of Iran, 17(2), 147–152.
[42] Wells, F. G., Cater, F. W., Jr., Rynearson, G. A. (1946). Chromite deposits of Del Norte County, California. California Division of Mines Bulletin, 134, 1–76.
[43] Abrams, M. J., Rothery, D. A., Pontual, A. (1988). Mapping in the Oman Ophiolite using enhanced Landsat Thematic Mapper images. Tectonophysics, 151, 387–401.
[44] Lipin, B. R. (1984). Chromite from the Blue Ridge Province of North Carolina. American Journal of Science, 284, 507–529.
[45] Fazliani, H., Rahimi Pour, Gh. R., Ranjbar, H. (2007). Investigation of mineral zoning in the Kadkan and Shamkan geological sheets using the stream sediment geochemical data. 26th Geoscience Conference. Geological Survey of Iran, Tehran.
[46] Hedenquist, J. W., Izawa, E., Arribas, A., White, N. C. (1996). Epithermal Gold Deposits: Styles, Characteristics, and Exploration. Society of Resource Geology of Japan.
[47] Simmons, S. F., White, N. C., JOHN, D. A. (2005). Geological Characteristics of Epithermal Precious and Base Metal Deposits: in: Hedenquist, J. W., Thompson, J. F. H., Goldfarb, R. J., and Richards, J. P., eds., Economic Geology 100th Anniversary Volume: The Economic Geology Publishing Company, 485–522
[48] Taylor, B. E. (2007). Epithermal gold deposits . in Goodfellow, W. D., ed., Mineral Deposits of Canada: A Synthesis of Major Deposit-Types, District Metallogeny, the Evolution of Geological Provinces, and Exploration Methods: Geological Association of Canada, Mineral Deposits Division, Special Publication No. 5, 113–139.
[49] Sawkins, F. J. (1990). Metal deposits in relation to plate tectonics. Berlin, Springer-Verlag, 461.
[50] Sillitoe, R. H., Hedenquist, J. W. (2003). Linkages between volcano-tectonic settings, ore fluid compositions, and epithermal precious metal deposits . Society of Economic Geologists Special Publication 10, 315–343.
[51] Bethke, P. M., Rye, R. O., Stoffregen, R. E., Vikre, P. G. (2005). Evolution of the magmatic-hydrothermal acid-sulfate system at Summitville, Colorado: Integration of geological, stable isotope, and fluid inclusion evidence. Chemical Geology, 215, 281–315.
[52] Arancibia, G., Matthews, S. J., Cornejo, P., Perez de Arce, C., Zuluaga, J. I., and Kasanevan, S. (2006). 40Ar/ 39Ar and K-Ar geochronology of magmatic and hydrothermal events in a classic low-sulphidation epithermal bonanza deposit; El Peñon, Northern Chile. Mineralium Deposita , 41, 505–516.
[53] Harvey, B., Myers, S., Klein, T. (1999). Yanacocha gold district, northern Peru. Pacific Rim Congress , Bali, Indonesia, Australasian Institute of Mining and Metallurgy, Proceedings, 445–459. | ||
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آمار تعداد مشاهده مقاله: 424 تعداد دریافت فایل اصل مقاله: 406 |
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