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Delineation of geochemical anomalies using factor analysis and multifractal modeling based on stream sediments data in Sarajeh 1:100,000 sheet, Central Iran

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Abstract

The aim of this study is to delineate the Cu, Au, and Pb anomalies in Sarajeh 1:100,000 sheet located in Urumieh-Dokhtar ore belt, central Iran. The analyzed elements of stream sediment samples taken in the area can be classified into six groups (factors) by factor analysis. The concentration–area and number–size multifractal inverse distance weighted models were applied for recognition of the elemental thresholds which are similar in both used multifractal models. According to the thresholds, the elemental concentration distribution for Cu, Au, and Pb were divided to three lithological classifications, namely mainly c alkaline porphyry with Cu–Au mineralization, mafic and sedimentary rocks. The results illustrate that the major anomalies of Cu, Au, Pb and related factors are mostly located around intrusions, volcanics, and along NW–SE faults.

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References

  • Afzal P, Fadakar Alghalandis Y, Khakzad A, Moarefvand P, Rashidnejad Omran N (2011) Delineation of mineralization zones in porphyry Cu deposits by fractal concentration–volume modeling. J Geochem Explor 108:220–232

    Article  Google Scholar 

  • Afzal P, Fadakar Alghalandis Y, Khakzad A, Moarefvand P, Rashidnejad Omran N, 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. J Geochem Explor 112:131–138

    Article  Google Scholar 

  • Afzal P, Khakzad A, Moarefvand P, Rashidnejad Omran N, Esfandiari B, Fadakar Alghalandis Y (2010) Geochemical anomaly separation by multifractal modeling in Kahang (GorGor) porphyry system, Central Iran. J Geochem Explor 104:34–46

    Article  Google Scholar 

  • Agterberg FP, Cheng Q, Wright DF (1993) Fractal modeling of mineral deposits. In: Elbrond J, Tang X (eds) 24th APCOM symposium proceeding, Montreal, Canada. Canadian Institute of Mining, Metallurgy and Petroleum Engineering, Montreal, pp 43–53

    Google Scholar 

  • Agterberg FP (1995) Multifractal modeling of the sizes and grades of giant and supergiant deposits. Int Geol Rev 37:1–8

    Article  Google Scholar 

  • Agterberg FP (2007) Mixtures of multiplicative cascade models in geochemistry. Nonlinear Proc Geoph 14:201–209

    Article  Google Scholar 

  • Alavi M (1994) Tectonics of Zagros Orogenic belt of Iran, new data and interpretation. Tectonophysics 229:211–238

    Article  Google Scholar 

  • Allègre CL, Lewin E (1995) Scale law scaling laws and geochemical distributions. Earth Planet Sci Lett 132:1–13

    Article  Google Scholar 

  • Bai J, Porwal A, Hart C, Ford A, Yu L (2010) Mapping geochemical singularity using multifractal analysis: application to anomaly definition on stream sediments data from Funin Sheet, Yunnan, China. J Geochernical Explor 104:1–11

    Article  Google Scholar 

  • Berberian M, King GC (1981) Towards a paleogeography and tectonic evolution of Iran. Can J Earth Sci 18:210–265

    Article  Google Scholar 

  • Bolviken B, Stokke PR, Feder J, Jossang T (1992) The fractal nature of geochemical landscapes. J Geochem Explor 43:91–109

    Article  Google Scholar 

  • Carranza EJM (2008) Geochemical anomaly and mineral prospectivity mapping in GIS. Handbook of exploration and environmental geochemistry, vol 11. Elsevier, Amsterdam, pp 1–351

    Google Scholar 

  • Carranza EJM (2009) Controls on mineral deposit occurrence inferred from analysis of their spatial pattern and spatial association with geological features. Ore Geol Rev 35:383–400

    Article  Google Scholar 

  • Carranza EJM, Sadeghi M (2012) Primary geochemical characteristics of mineral deposits—implications for exploration. Ore Geol Rev 45:1–4

    Article  Google Scholar 

  • Cheng Q (1999) Spatial and scaling modeling for geochemical anomaly separation. J Geochem Explor 65:175–194

    Article  Google Scholar 

  • Cheng Q (2008) Modeling local scaling properties for multiscale mapping. Vadose Zone J 7:525–532

    Article  Google Scholar 

  • Cheng Q, Agterberg FP, Ballantyne SB (1994) The separation of geochemical anomalies from background by fractal methods. J Geochem Explor 51:109–130

    Article  Google Scholar 

  • Dargahi S, Arvin M, Pan Y, 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 115:190–204

    Article  Google Scholar 

  • Davis JC (2002) Statistics and data analysis in geology. Wiley, New York, pp 1–638

    Google Scholar 

  • Deng J, Wang Q, Yang L, Wang Y, Gong Q, Liu H (2010) Delineation and explanation of geochemical anomalies using fractal models in the Heqing area, Yunnan Province, China. J Geochem Explor 105:95–105

    Article  Google Scholar 

  • Filzmoser P, Hron K, Reimann C (2009) Principal component analysis for compositional data with outliers. Environ Sci Technol 20(6):621–632

    Google Scholar 

  • Filzmoser P, Todorov V (2011) Review of robust multivariate statistical methods in high dimension. Anal Chim Acta 705:2–14

    Article  Google Scholar 

  • Gałuszk A (2007) A review of geochemical background concepts and an example using data from Poland. Environ Geol 52(5):861–870

    Article  Google Scholar 

  • Goncalves MA, Mateus A, Oliveira V (2001) Geochemical anomaly separation by multifractal modeling. J Geochem Explor 72:91–114

    Article  Google Scholar 

  • Grunsky EC, Drew LJ, Sutphin DM (2009) Process recognition in multi-element soil and stream-sediment geochemical data. Appl Geochem 24:1602–1616

    Article  Google Scholar 

  • Hashemi M, Afzal P (2012) Identification of geochemical anomalies by using of number–size (N–S) fractal model in Bardaskan area, NE Iran. Arab J Geosci. doi:10.1007/s12517-012-0657-8

    Google Scholar 

  • Hassanpour S, Afzal P (2013) Application of concentration–number (C–N) multifractal modeling for geochemical anomaly separation in Haftcheshmeh porphyry system, NW Iran. Arab J Geosci 6:957–970

    Google Scholar 

  • Hawkes HE, Webb JS (1962) Geochemistry in mineral exploration. Harper and Row, New York, pp 1–415

    Google Scholar 

  • Hawkes HE, Webb JS (1979) Geochemistry in mineral exploration, 2nd edn. Academic, New York, pp 1–657

    Google Scholar 

  • Johnson RA, Wichern DW (2002) Applied multivariate statistical analysis, 5th edn. Prentice Hall, Upper Saddle River

    Google Scholar 

  • Jolliffe IT (2002) Principal component analysis, 2nd edn. Springer, New York, pp 1–487

    Google Scholar 

  • Krumbein WC, Graybill FA (1965) An introduction to statistical models in geology. McGraw-Hill, New York

    Google Scholar 

  • Li CJ, Ma TH, Shi JF (2003) Application of a fractal method relating concentration and distances for separation of geochemical anomalies from background. J Geochem Explor 77:167–175

    Article  Google Scholar 

  • Li C, Xu Y, Jiang X (1994) The fractal model of mineral deposits. Geology of Zhejiang 10:25–32 (In Chinese with English Abstract)

    Google Scholar 

  • Lima A, De Vivo B, Cicchella D, Cortini M, Albanese S (2003) Multifractal IDW interpolation and fractal filtering method in environmental studies: an application on regional stream sediments of (Italy), Campania region. Appl Geochem 18(12):1853–1865

    Article  Google Scholar 

  • Mandelbrot BB (1983) The fractal geometry of nature. Freeman, San Francisco, pp 1–468

    Google Scholar 

  • Meng X, Zhao P (1991) Fractal method for statistical analysis of geological data. Chinese J Geosci 2:207–211

    Google Scholar 

  • Mohammadi A, Khakzad A, Rashidnejad Omran N, Mahvi MR, Moarefvand P, Afzal P (2012) Application of number–size (N–S) fractal model for separation of mineralized zones in Dareh-Ashki gold deposit, Muteh Complex, Central Iran. Arab J Geosci. doi:10.1007/s12517-012-0662-y

    Google Scholar 

  • Monecke T, Monecke J, Herzig PM, Gemmell JB, Monch W (2005) Truncated fractal frequency distribution of element abundance data: a dynamic model for the metasomatic enrichment of base and precious metals. Earth Planet Sci Lett 232:363–378

    Article  Google Scholar 

  • Muller J, Kylander M, Martinez-Cortizas A, Wüst RAJ, Weiss D, Blake K, Coles B, Garcia-Sanchez R (2008) The use of principle component analyses in characterizing trace and major elemental distribution in a 55 kyr peat deposit in tropical Australia: implications to paleoclimate. Geochim Cosmochim Ac 72:449–463

    Article  Google Scholar 

  • Pazand K, Hezarkhani A, Ataei M, Ghanbari Y (2011) Application of multifractal modeling technique in systematic geochemical stream sediment survey to identify copper anomalies: a case study from Ahar, Azarbaijan, Northwest Iran. Chem Erde 71:397–402

    Article  Google Scholar 

  • Rantitsch G (2000) Application of fuzzy clusters to quantify lithological background concentrations in stream-sediment geochemistry. J Geochem Explor 71:73–82

    Article  Google Scholar 

  • Reimann C, Filzmoser P, Garrett RG (2005) Background and threshold: critical comparison of methods of determination. Sci Total Environ 346:1–16

    Article  Google Scholar 

  • Rousseeuw P, Van Driessen K (1999) A fast algorithm for the minimum covariance determinant estimator. Technometrics 41(3):212–223

    Article  Google Scholar 

  • Sadeghi B, Moarefvand P, Afzal P, Yasrebi AB, Daneshvar Saein L (2012a) Application of fractal models to outline mineralized zones in the Zaghia iron ore deposit, Central Iran. J Geochem Explor, Special Issue “fractal/multifractal modelling of geochemical data”, 122:9–19

  • Sadeghi B, Afzal P, Moarefvand P, KhodaShenas N (2012b) Application of concentration–area fractal method for determination of Fe geochemical anomalies and the background in Zaghia area, Central Iran. 34th International Geological Congress (IGC), Brisbane, Australia

  • Sanderson DJ, Roberts S, Gumiel P (1994) A fractal relationship between vein thickness and gold grade in drill core from La Codosera, Spain. Econ Geol 89:168–173

    Article  Google Scholar 

  • Shahabpour J (1994) Post-mineral brecciadyke from the Sar-Cheshmehporphyry copper deposit, Kerman, Iran. Explor Min Geol 3:39–43

    Google Scholar 

  • Shi J, Wang C (1998) Fractal analysis of gold deposits in China: implication for giant deposit exploration Earth Sciences. J China Univ Geosci 23:616–618 (In Chinese with English Abstract)

    Google Scholar 

  • Stanley CR, Sinclair AJ (1989) Comparison of probability plots and gap statistics in the selection of threshold for exploration geochemistry data. J Geochem Explor 32:355–357

    Article  Google Scholar 

  • Tehran Padir Co. (2005) Regional geochemical exploration report in Sarajeh 1:100000 sheet. Tehran Padir Co., Tehran

  • Tripathi VS (1979) Factor analysis in geochemical exploration. J Geochem Explor 11:263–275

    Article  Google Scholar 

  • Tukey JW (1997) Exploratory data analysis. Addison-Wesley, Reading

    Google Scholar 

  • Turcotte DL (1986) A fractal approach to the relationship between ore grade and tonnage. Econ Geol 18:1525–1532

    Google Scholar 

  • Turcotte DL (1997) Fractals and chaos in geology and geophysics. Cambridge University Press, Cambridge, pp 1–398

    Book  Google Scholar 

  • Wang QF, Deng J, Wan L, Zhao J, Gong QJ, Yang LQ, Zhou L, Zhang ZJ (2008) Multifractal analysis of the element distribution in skarn-type deposits in Shizishan Orefield in Tongling area, Anhui province, China. Acta Geol Sin 82:896–905

    Google Scholar 

  • Yousefi M, Kamkar-Rouhani A, Carranza EJM (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. J Geochem Explor 115:24–35

    Article  Google Scholar 

  • Zuo R (2011a) 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). J Geochem Explor 111:13–22

    Article  Google Scholar 

  • Zuo R (2011b) Decomposing of mixed pattern of arsenic using fractal model in Gangdese belt, Tibet, China. Appl Geochem 26:S271–S273

    Article  Google Scholar 

  • Zuo R, Cheng Q, Xia Q (2009) Application of fractal models to characterization of vertical distribution of geochemical element concentration. J Geochem Explor 102:37–43

    Article  Google Scholar 

  • Zuo R, Xia Q (2009) Application fractal and multifractal methods to mapping prospectivity for metamorphosed sedimentary iron deposits using stream sediment geochemical data in eastern Hebei province, China. Geochim Cosmochim Ac 73:A1540–A1540

    Google Scholar 

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Acknowledgments

The authors would like to thank Mr. Reza Zarinfar, the manager of Parsi Kan Kav Co., for authorizing the use of Sarajeh exploration data. Moreover, the authors would like to thank Dr. Renguang Zuo for his comments and valuable remarks.

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Authors and Affiliations

  1. Department of Mining Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran

    Mojtaba Shamseddin Meigoony, Peyman Afzal, Mehran Gholinejad & Behnam Sadeghi

  2. Camborne School of Mines, University of Exeter, Penryn, UK

    Peyman Afzal & Amir Bijan Yasrebi

  3. Young Researchers Club, South Tehran Branch, Islamic Azad University, Tehran, Iran

    Mojtaba Shamseddin Meigoony

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  1. Mojtaba Shamseddin Meigoony
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  2. Peyman Afzal
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  3. Mehran Gholinejad
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  4. Amir Bijan Yasrebi
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  5. Behnam Sadeghi
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Correspondence to Peyman Afzal.

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Meigoony, M.S., Afzal, P., Gholinejad, M. et al. Delineation of geochemical anomalies using factor analysis and multifractal modeling based on stream sediments data in Sarajeh 1:100,000 sheet, Central Iran. Arab J Geosci 7, 5333–5343 (2014). https://doi.org/10.1007/s12517-013-1074-3

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