Skip to main content
SpringerLink
Log in

Applying a Structural Multivariate Method Using the Combination of Statistical Methods for the Delineation of Geochemical Anomalies

  • Research Paper
  • Published:
Iranian Journal of Science and Technology, Transactions A: Science Aims and scope Submit manuscript

Abstract

Quantitative descriptions of geochemical patterns and providing geochemical anomaly map are important in applied geochemistry. Several statistical methodologies (nonstructural and structural) are presented in order to identify and separate geochemical anomalies. Structural methods take the sampling locations and their spatial relation into account for estimating the anomalous areas. In the present study, a nonstructural method (Mahalanobis distance method as a multivariate method) is used and U-statistic is considered as a structural method to assess prospective areas of Susanvar district as a gold mineralization index in the Torud-Chah Shirin mountain range of Semnan Province, northern Iran. Results show that the U-statistic method is an efficient method according to spatial distribution of the anomalous samples. In the present study, according to the ability of U-statistic method in combining with other methods, the goal is to use and develop Mahalanobis distance method in structural mode. For this purpose, Mahalanobis distance should be combined with a structural method which devotes a new value to each sample based on its surrounding samples. For this reason, the combination of efficient U-statistic method and multivariate Mahalanobis distance method has been used to separate geochemical anomalies from background. Combination results show that the performance of these two methods is more accurate than using just one of them. Because samples indicated by the combination of these methods as anomalous are less dispersed and closer to each other than in the case of using just the U-statistic and other nonstructural methods such as Mahalanobis distance. Also it was observed that the combination results are closely associated with the defined Au ore indication within the study area. Finally, univariate and bivariate geochemical anomaly maps are provided for Au and As, which have been, respectively, prepared using U-statistic and its combination with Mahalanobis distance method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

References

  • Alavi M (1991) Tectonic map of the Middle East: Geological Survey of Iran, Tehran

  • Bodenan F, Baranger P, Piantone P, Lassin A, Azaroual M, Gaucher E, Braibant G (2004) Arsenic behaviour in gold-ore mill tailings, Massif Central, France: hydrogeochemical study and investigation of in situ redox signatures. Appl Geochem 19:1785–1800

    Article  Google Scholar 

  • Cheng Q (1999) Spatial and scaling modelling for geochemical anomaly separation. J Geochem Explor 65(3):175–194

    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 

  • Cheng Q, Agterberg FP, Bonham-Carter GF (1996) A spatial analysis method for geochemical anomaly separation. J Geochem Explor 56:183–195

    Article  Google Scholar 

  • Filzmoser P, Garrett RG, Reimann C (2005) Multivariate outlier detection in exploration geochemistry. Comput Geosci 31:579–587

    Article  Google Scholar 

  • Geological Survey of Iran (1995) Explanatory text of geochemical map of Moaleman (6960). Report 1(9):33

  • Ghannadpour SS, Hezarkhani A (2012) Developed software to calculate the additive constant number of average in three-variable normal logarithm. Glob J Comput Sci 2(1):7–13

    Google Scholar 

  • Ghannadpour SS, Hezarkhani A (2015a) Lead and zinc geochemical behavior based on geological characteristics in Parkam Porphyry Copper System, Kerman, Iran. J Cent South Univ 22(11):4274–4290

    Article  Google Scholar 

  • Ghannadpour SS, Hezarkhani A (2015b) Investigation of Cu, Mo, Pb, and Zn geochemical behavior and geological interpretations for Parkam porphyry copper system, Kerman, Iran. Arab J Geosci 8(9):7273–7284

  • Ghannadpour SS, Hezarkhani A (2016a) Introducing 3D U-statistic method for separating anomaly from background in exploration geochemical data with associated software development. J Earth Syst Sci 125(2):387–401

    Article  Google Scholar 

  • Ghannadpour SS, Hezarkhani A (2016b) Exploration geochemistry data-application for anomaly separation based on discriminant function analysis in the Parkam porphyry system (Iran). Geosci J 20(6):837–850

    Article  Google Scholar 

  • Ghannadpour SS, Hezarkhani A (2017a) Comparing U-statistic and nonstructural methods for separating anomaly and generating geochemical anomaly maps of Cu and Mo in Parkam district, Kerman, Iran. Carbon Evapor 32(2):155–166

    Article  Google Scholar 

  • Ghannadpour SS, Hezarkhani A (2017b) Providing the bivariate anomaly map of Cu–Mo and Pb–Zn using combination of statistic methods in Parkam district, Iran. Carbon Evapor. https://doi.org/10.1007/s13146-017-0349-2

    Article  Google Scholar 

  • Ghannadpour SS, Hezarkhani A, Eshqi H (2012) Average and variance estimation programming in normal logarithmic distribution. Glob J Comput Sci 2(1):1–6

    Google Scholar 

  • Ghannadpour SS, Hezarkhani A, Sabetmobarhan A (2015a) Some statistical analyses of Cu and Mo variates and geological interpretations for Parkam porphyry copper system, Kerman, Iran. Arab J Geosci 8(1):345–355

    Article  Google Scholar 

  • Ghannadpour SS, Hezarkhani A, Maghsoudi A, Farahbakhsh E (2015b) Assessment of prospective areas for providing the geochemical anomaly maps of lead and zinc in Parkam district, Kerman, Iran. Geosci J 19(3):341–440

    Article  Google Scholar 

  • Ghannadpour SS, Hezarkhani A, Sabetmobarhan A (2017a) The Parkam exploration district (Kerman, Iran): geology, alterations, and delineation of Cu- and Mo-mineralized zones using U-spatial statistic with associated software development. J Earth Sci 28(2):283–294

    Article  Google Scholar 

  • Ghannadpour SS, Hezarkhani A, Roodpeyma T (2017b) Combination of separation methods and data mining techniques for prediction of anomalous areas in Susanvar, Central Iran. J African Earth Sci 134:516–525

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Hassanzadeh J, Ghazi AV, Axen G, Guest B (2002) Oligomiocene mafic-alkaline magmatism in north and northwest of Iran: evidence for the separation of the Alborz from the Urumieh-Dokhtar magmatic arc. Geol Soc Am Abstr Program 34(6):331

    Google Scholar 

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

    Google Scholar 

  • Hezarkhani A, Ghannadpour SS (2015) Geochemical behavior investigation based on K-means clustering (basics, concepts and case study), 1st edn. LAP LAMBERT Academic Publishing, Berlin

    Google Scholar 

  • Kazmin VG, Sborshikov IM, Ricou LE, Zorenshain EP, Boulin S, Knipper AL (1986) Volcanic belts as markers of the Mesozoic–Cenozoic active margin of Eurasia. Tectonophysics 123:123–152

    Article  Google Scholar 

  • Miesch AT (1981) Estimation of the geochemical threshold and its statistical significance. J Geochem Explor 16:49–76

    Article  Google Scholar 

  • Moeini H, Aryafar A (2016) Local multivariate outliers as geochemical anomaly halos indicators, a case study: Hamich area, Southern Khorasan, Iran. J Mining Environ https://doi.org/10.22044/jme.2016.656

  • Morrison GW, Rose WJ, Jaireth S (1991) Geological and geochemical controls on the silver content (fineness) of gold in gold-silver deposits. Ore Geol Rev 6:333–364

    Article  Google Scholar 

  • Ramzan S, Zahid FM, Ramzan S (2013) Evaluating multivariate normality: a graphical approach. Middle-East J Sci Res 13(2):254–263

    Google Scholar 

  • Shamanian GH, Hedenquist JW, Hattori KH, Hassanzadeh J (2003) Epithermal precious- and base-metal mineralization in the Eocene arc of Torud-Chah Shirin mountain range: Gandy and Abolhassani districts, Semnan, northern Iran. In: Eliopoulos DG et al (eds) Mineral exploration and sustainable development. Millpress, Rotterdam, pp 519–522

    Google Scholar 

  • Shamanian GH, Hedenquist JW, Hattori KH, Hassanzadeh J (2004) The Gandy and Abolhassani epithermal deposits in the Alborz magmatic arc, Semnan Province, northern Iran. Econ Geol 99(4):691–712

    Article  Google Scholar 

  • Sinclair AJ (1991) A fundamental approach to threshold estimation in exploration geochemistry: probability plots revisited. J Geochem Explor 41(1):1–22

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Thornton I, Farago M (1997) The geochemistry of arsenic. In: Abernathy CO, Calderon RL, Chappell WR (eds), Arsenic exposure and health effects, Chapman & Hall, London, pp 1–16

  • 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). J Geochem Explor 111:13–22

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mining and Metallurgical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran

    Seyyed Saeed Ghannadpour, Ardeshir Hezarkhani & Fatemeh Ghashghaei

  2. Department of Mining Engineering and Metallurgical Engineering, Western Australia School of Mine, Curtin University, Kalgoorlie, WA, Australia

    Mostafa Sharifzadeh

Authors
  1. Seyyed Saeed Ghannadpour
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ardeshir Hezarkhani
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mostafa Sharifzadeh
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fatemeh Ghashghaei
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ardeshir Hezarkhani.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ghannadpour, S.S., Hezarkhani, A., Sharifzadeh, M. et al. Applying a Structural Multivariate Method Using the Combination of Statistical Methods for the Delineation of Geochemical Anomalies. Iran J Sci Technol Trans Sci 43, 127–140 (2019). https://doi.org/10.1007/s40995-017-0452-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40995-017-0452-1

Keywords

Search

Navigation