Porphyry copper prospectivity mapping using fuzzy and fractal modeling in Sonajeel area, NW Iran

Yıl 2019, , 235 - 250, 25.04.2019

Zahra Yazdi Alireza Jafari Rad , Mehraj Aghazadeh Peyman Afzal

https://doi.org/10.19111/bulletinofmre.391835

Öz

Main purpose of this
research is to present a local scale GIS-based mineral prospectivity model for prospecting
Cu porphyry mineralization, and to validate the produced model by field observation,
surface sampling and drilling data. Sonajeel area which is the subject of this study
is a part of Arasbaran mineralization belt, NW of Iran. Constructing a mathematical
exploratory algorithm based on a mineralization type is a complicated and interdisciplinary
task. For this purpose, results from processing and interpreting different data
sets including geology, geochemistry and remote sensing were considered. A comprehensive
exploratory integration model was built up considering the exploration stage and
the descriptive porphyry mineralization model suggested by Sillitoe (2010). In order
to prepare inputs for GIS-based exploration model, value assigned grids or evidence
layers were produced using fuzzy membership curves and then integrated via gamma
fuzzy function. In addition, for defuzzification and prioritizing the mineral prospectivity
map, a Concentration- Area (C-A) fractal model was applied on the pixel values of
the prospectivity map. Finally, the results were confirmed via field observation,
surface sampling and drilling. Borehole logs at the first priority displayed a Cu
mineralization zone with an average grade of 0.5%.

Anahtar Kelimeler

Fuzzy logic, GIS, fractal, prospectivity map, porphyry copper, sonajeel

Kaynakça

• Abdi, H., Williams L.J. 2010. Principal Component Analysis. Wiley Interdisciplinary Reviews: Computational Statistics 2, 433-459.
• Abedi, M., Mostafavi Kashani, S. B., Norouzi, G. H., Yousefi, M. 2017. A deposit scale mineral prospectivity analysis: A comparison of various knowledge-driven approaches for porphyry copper targeting in Seridune, Iran. Journal of African Earth Sciences 128, 127-146.
• Afzal, P., Khakzad, A., Moarefvand, P., Rashidnejad Omran, N., Esfandiari, B., Fadakar Alghalandis, Y. 2010. Geochemical anomaly separation by multifractal modeling in Kahang (Gor Gor) porphyry system, Central Iran. Journal of Geochemical Exploration 104, 34-46.
• Afzal, P., Zarifi, A. Z., Khankandi, S. F., Wetherelt, A., Yasrebi, A. B. 2012. Separation of uranium anomalies based on geophysical airborne analysis by using Konsantrasyon-Alan (C-A) Fractal Model, Mahneshan 1:50000 Sheet, NW IRAN. Journal of Mining and Metallurgy 48A(1), 1-11.
• Aghazadeh, M., Hou, Z., Badrzadeh, Z., Zhou, L. 2015. Temporal-spatial distribution and tectonic setting of porphyry copper deposits in Iran: Constraints from zircon U-Pb and molybdenite Re-Os geochronology. Ore Geology Reviews 70, 385- 406.
• Aghazadeh, M. 2014. Geological report of Sonajeel (1:5000), Koome Madan Company.
• Agterberg, F.P., Bonham-Carter, G.F., Wright, D.F. 1990. Statistical pattern integration for mineral exploration. In: Gaal G., Merriam D.F. (Eds.), Computer Applications in Resource Estimation Prediction and Assessment for Metals and Petroleum. Pergamon Press, Oxford New York, 1-21.
• Alimohammadi, M., Alirezaei, S., Kontak, D.J. 2015. 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 70, 290-304. Almasi, A., Jafarirad, A., Afzal, P., Rahimi, M. 2015a. Prospecting of gold mineralization in Saqez area (NW Iran) using geochemical, geophysical and geological studies based on multifractal modelling and principal component analysis. Arabian Journal of Geosciences 8(8), 5935-5947.
• Almasi, A., Jafarirad, A., Kheirollahi, H., Rahimi, M., Afzal, P. 2015b. Orogenic Gold Prospectivity Mapping of Region Saqez, Bulletin of the Mineral Research and Exploration 150, 65-76.
• Almasi, A., Yousefi, M., Carranza, E.J.M. 2017. Prospectivity analysis of orogenic gold deposits in Saqez-Sardasht Goldfield, Zagros Orogen, Iran. Ore Geology Reviews 91, 1066-1080.
• An, P., Moon, W.M., Rencz, A. 1991. Application of fuzzy set theory to integrated mineral exploration. Canadian Journal of Exploration Geophysics, 27(1), 1-11.
• Babaie, H.A., Ghazi, A.M., Babaei, A., La Tour, T.E., Hassanipak, A.A. 2001. Geochemistry of arc volcanic rocks of the Zagros crush zone, Neyriz, Iran. Journal of Asian Earth Sciences 19, 61-76.
• Beane, R. E. 1982. Hydrothermal alteration in silicate rocks, in Titley S. R., ed., Advances in geology of the porphyry copper deposits, southwestern North America: Tucson. The University of Arizona Press, pp. 117-137.
• Berberian, M., King, G.C. 1981. Towards a paleogeography and tectonic evolution of Iran. Canadian Journal of Earth Sciences 18, 210-265.
• Berger, B.R., Ayuso, R.A., Wynn, J.C., Seal, R.R. 2008. Preliminary Model of Porphyry Copper Deposits. USGS, Open-File Report, 1321 pp.
• Bishop, C.M. 2006. Pattern Recognition and Machine Learning. Springer: New York, NY, USA, 738 pp.
• Bonham-Carter, G.F., Agterberg, F.P., Wright, D.F. 1989. Weights of evidence modelling: new approach to mapping mineral potential In: Agterberg F. P., Bonham-Carter G. F. (Eds.), Statistical Applications in the Earth Sciences Geological Survey of Canada, 171-183.
• Bonham-Carter, G.F. 1994. Geographic Information Systems for Geoscientists: Modeling with GIS. Pergamon Press, Ontario, Canada, 398 pp.
• Byron, R., Berger Robert, A. 2008. Preliminary model of porphyry copper deposits, U.S. Geological survey 3.
• Carranza, E. J. M. 2008. Geochemical anomaly and mineral prospectivity mapping in GIS. Handbook of Exploration and Environmental Geochemistry, Vol. 11. Elsevier, Amsterdam.
• Carranza, E.J.M. 2009a. Mapping of anomalies in continuous and discrete fields of stream sediment geochemical landscapes. Geochemistry: Exploration, Environment, Analysis 10, 171-187.
• Carranza, E.J.M. 2009b. Controls on mineral deposit occurrence inferred from analysis of their spatial pattern and spatial association with geological features. Ore Geology Reviews 35, 383-400.
• Carranza, E.J.M. 2010. Improved Wildcat Modelling of Mineral Prospectivity. Resource Geology 60(2), 129-149.
• Carranza, E.J.M. 2014. Data-driven evidential belief modeling of mineral potential using few prospects and evidence with missing values. Natural Resources 24(3), 291-304.
• Carranza, E.J.M., Hale, M. 2002. Mineral mapping with Landsat thematic mapper data for hydrothermal alteration mapping in heavily vegetated terrane. International Journal of Remote Sensing 23(22), 4827-4852.
• Cheng, Q., Agterberg, F. P., Ballantyne, S. B. 1994. The separation of geochemical anomalies from background by fractal methods. Journal of Geochemical Exploration 51(2), 109-130.
• Chung, C.F., Agterberg, F. P. 1980. Regression models for estimating mineral resources from geological map data. Mathematical Geology 12(5), 472-488.
• Chung, C.F., Moon, W. M. 1990. Combination rules of spatial geoscience data for mineral exploration. Geoinformatics 2, 159-169.
• Davis, J.C. 2002. Statistics and Data Analysis in Geology, 3rd edn. John Wiley & Sons Inc, New York, pp. 342-353.
• Deng, J., Wang, Q.F., Wan, L., Yang, L.Q., Liu, X.F. 2007. Singularity of Au distribution in alteration rock type deposit, an example from Dayingezhuang gold ore deposit. In: Zhao P.D., Agterberg F., Cheng Q.M. (Eds.), The 12th Conference of the International Association for Mathematical Geology, China University of Geosciences Press, Wuhan, pp. 44-47.
• Deng, J., Wang, Q. F., Wan, L., Yang, L. Q., Zhou, L., Zhao, J. 2008. The random difference of the trace element distribution in skarn and marbles from Shizishan ore field, Anhui Province, China. Journal of China University of Geosciences 19(4), 123-137.
• Ford, A., Miller, J. M., Mol, A.G. 2015. A comparative analysis of weights of evidence, evidential belief functions, and fuzzy logic for mineral potential mapping using incomplete data at the scale of investigation. Natural Resources Research 25, 19-33. Hassanpour, Sh., Afzal, P. 2013. Application of concentration-number (C-N) multifractal modelling for geochemical anomaly separation in Haftcheshmeh porphyry system, NW Iran. Arabian Journal of Geosciences 6(3), 957-970.
• Hezarkhani, A. 2008. Hydrothermal Evolution of the Sonajil Porphyry Copper System, East Azarbaijan Province, Iran: The History of an Uneconomic Deposit. International Geology Review 50(5), 483-501.
• Hosseinzadeh, G. H., Mouayed, M., Esfehanipour, R. 2009. Supergene Processes in Sonajil Porphyry Copper Deposit With Respect To Using Of Leached Capping For Estimation of Supergene Enrichment in Porphyry Copper Deposits. Iranian Journal Of Geology Summer, Volume 3, Number 10; Page(s) 85 To 96.
• Hosseinzadeh, M.R., Maghfouri,, S., Ghorbani, M., Moayyed, M. 2017. Different types of vein- veinlets related to mineralization and fluid inclusion studies in the Sonajil porphyry Cu- Mo deposit, Arasbaran magmatic zone. Scientific Quarterly Journal geosciences 26(101), 219-230.
• Jafarirad, A. 2009. Modeling of conceptual and empirical geospatial datasets for mineral prospecting mapping. PhD thesis, TUC, Germany, 190 pp.
• Jafarirad, A., Busch, W. 2011. Porphyry copper prospectivity mapping using interval valued fuzzy sets TOPSIS method in Central Iran. International Journal of Geographical Information Science 3, 312–317.
• Jamali, H., Mehrabi, B. 2015. Relationships between arc maturity and Cu-Mo-Au porphyry and related epithermal mineralization at the Cenozoic Arasbaran Magmatic Belt. Ore Geology Reviews 65(2), 487-501.
• Joly, A., Porwal A., McCuaig, T.C. 2012. Exploration targeting for orogenic gold deposits in the Granites-Tanami Orogen: Mineral system analysis, targeting model and prospectivity analysis. Ore Geology Reviews 48, 349-383.
• Karimi, M., Valadan Zoj, M.J. 2009. Mineral Potential Modeling of Sonajil Copper Prospect Using Fuzzy logic and GIS. Materials and Energy. Quarterly Journal of Science Kharazmi University 8(3), 265-282.
• Karimzadeh Somarin, A. 2005. Petrology and geochemistry of early tertiary volcanism of the Mendejin area, Iran, and implications for magma genesis and tectonomagmatic setting. Geodinamica Acta 18(5), 343-362.
• Lisitsin, V.A., González-Álvarez, I., Porwal, A. 2013. Regional prospectivity analysis for hydrothermal- remobilized nickel mineral systems in western Victoria, Australia. Ore Geology Reviews 52,100- 112.
• Lowell, J.D., Guilbert, J.M. 1970. Lateral and vertical alteration-mineralization zoning in porphyry ore deposits. Economic Geology 65(4), 373-408.
• Lusty, P.A.J., Scheib, C., Gunn, A.G., Walker, A.S.D. 2012. Reconnaissance-scale prospectivity analysis for gold mineralization in the Southern Uplands- Down-Longford Terrane, Northern Ireland. Natural Resources Research 21(3), 359-382.
• Magalhaes, L.A., Souza Filho, C.R. 2012. Targeting of gold deposits in Amazonian exploration frontiers using knowledge- and data-driven spatial modeling of geophysical, geochemical and geological data. Surveys in Geophysics 33(2), 211-214.
• McInnes, B.I.A., Evans, N.J., Belousova, E., Griffin, W.T., Andrew R. L. 2003. Timing of mineralization and exhumation processes at the Sar Cheshmeh and Meiduk porphyry Cu deposits, Kerman belt, Iran. In: Eliopoulos, vd. (Eds.), Mineral Exploration and Sustainable Development (7th Biennial SGA Meeting, Athens (August 24–28). Millpress, Rotterdam, pp. 1197-1200
• Meyer C., Hemley, J.J. 1967. Wall rock alteration, in Barnes H. L. ed., Geochemistry of hydrothermal ore deposits: New York, Holt, Rinehart and Winston, p. 166-235.
• Nykanen, V., Groves, D.L., Ojala, V.J., Eilo, P., Gardoll, S. J. 2008. Reconnaissance scale conceptual fuzzy-logic prospectivity modelling for iron oxide copper-gold deposits in the northern Fennoscandian Shield, Finland. Australian Journal of Earth Sciences 55(1), 25-38.
• Parsa, M., Maghsoudi, A., Yousefi, M., Sadeghi, M. 2016. Prospectivity modeling of porphyry-Cu deposits by identification and integration of efficient mono-elemental geochemical signatures. Journal of African Earth Sciences 114, 228-241.
• Parsa, M., Maghsoudi, A., Yousefi, M. 2017. An improved data-driven fuzzy mineral prospectivity mapping procedure; cosine amplitude-based similarity approach to delineate exploration targets. International Journal of Applied Earth Observation and Geoinformation 58, 157-167.
• Pazand, K., Hezarkhani, A., Ataei, M. 2012. Using TOPSIS approaches for predictive porphyry Cu potential mapping: A case study in Ahar-Arasbaran area (NW, Iran), Computers & Geosciences 49 (2012) 62–71.
• Pazand, K., Hezarkhani A., Ataei, M. 2013. The application of lithogeochemical and alteration index for copper mineralization in the Sonajil area, NW Iran. Arabian Journal of Geosciences 6(5), 1447- 1456.
• Porwal, A., Kreuzer, O.P. 2010. Introduction to the Special Issue: Mineral prospectivity analysis and quantitative resource estimation. Ore Geology Reviews 38(3), 121-127. Porwal, A., Carranza, E.J.M. 2015. Introduction to the Special Issue: GIS-based mineral potential modelling and geological data analyses for mineral exploration. Ore Geology Reviews 71, 477-483.
• Richards, J.P. 2015. Tectonic, magmatic, and metallogenic evolution of the Tethyan orogen: From subduction to collision. Ore Geology Reviews 70, 323-345.
• Richards, J. P., Sholeh, A. 2016. Chapter 7- The Tethyan Tectonic History and Cu-Au Metallogeny of Iran. Economic Geologists, Inc. Special Publication 19, 193-212.
• Seedorff, E., Dilles, J.H., Phoffett, Jr., J.M., Einaudi, M. T., Zurcher, L., Stavast, W. J.A., Johnson, D. A., Barton, M. D. 2005. Porphyry deposits: Characteristics and origin of hypogene features. Littleton. Economic Geology One Hundredth Anniversary Volume, 251-298.
• Sillitoe, R.H. 2010. Porphyry copper systems. Economic Geology 105, 3-41.
• Shahabpour, J., Kramers, J.D. 1987. Lead isotope data from the Sar Cheshmeh porphyry copper deposit, Kerman. Iran. Mineralium Deposita 22, 278-281.
• Stocklin, J. 1974. Possible ancient continental margins in Iran. In: Burk, C.A., Drake, C.L. (Eds.), The Geology of Continental Margins. Springer, Berlin, pp. 873-887.
• Tsoukalas, L.H., Uhrig, R.E. 1997. Fuzzy and neural approaches in engineering. Wiley, New York, p 587.
• Wang, Y.M., Chin, K.S. 2011. Fuzzy data envelopment analysis: A fuzzy expected value approach. Expert Systems with Applications 38(9), 11678-11685.
• Wang, G., Zhu, Y., Zhang, S., Yan, C., Song, Y., Ma, Z., Hong, D., Chen T. 2012. 3D geological modeling based on gravitational and magnetic data inversion in the Luanchuan ore region, Henan Province, China. Journal of Applied Geophysics 80, 1-11. Wang, G., Pang, Z., Boisvert, J.B., Hao, Y., Cao, Y., Qu, J. 2013. Quantitative assessment of mineral resources by combining geostatistics and fractal methods in the Tongshan porphyry Cu deposit (China). Journal of Geochemical Exploration 134, 85-98.
• Wang, W., Zhao, J., Cheng, Q., Carranza, E.J.M. 2014. GIS- based mineral potential modeling by advanced spatial analytical methods in the southeastern Yunnan mineral district, China. Ore Geology Reviews 71, 735-748.
• Yazdi, Z., Jafarirad, A.R., Ajayebi, K.S. 2014. Analysis and modeling of geospatial datasets for porphyry copper prospectivity mapping in Chahargonbad area, Central Iran. Arabian Journal of Geosciences 8(10), 8237-8248.
• Yousefi, M. 2017. Recognition of an enhanced multi- element geochemical signature of porphyry copper deposits for vectoring into mineralized zones and delimiting exploration targets in Jiroft area, SE Iran. Ore Geology Reviews 83, 200-214.
• Yousefi, M., Kamkar-Rouhani, A., Carranza, E.J.M. 2012. 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. Journal of Geochemical Exploration 115, 24-35.
• Yousefi, M., Carranza, E.J.M., Kamkar-Rouhani, A. 2013. Weighted drainage catchment basin mapping of stream sediment geochemical anomalies for mineral potential mapping. Journal of Geochemical Exploration 128, 88-96.
• Yousefi, M., Carranza, E.J.M. 2014. Data-driven index overlay and Boolean logic mineral prospectivity modeling in greenfields exploration. Natural Resources Research 25(1), 3-18.
• Yousefi, M., Carranza, E.J.M. 2015a. Fuzzification of continuous-value spatial evidence for mineral prospectivity mapping. Computers & Geosciences 74, 97-109.
• Yousefi, M., Carranza, E.J.M. 2015b. Prediction-area (P- A) plotand C-A fractal analysis to classify and evaluate evidential maps for mineral prospectivity modeling. Computers & Geosciences 79, 69–81.
• Yousef, M., Nykanen, V. 2016. Data-driven logistic- based weighting of geochemical and geological evidence layers in mineral prospectivity mapping. Journal of Geochemical Exploration 164, 94-106.