Abstract
In applied geochemistry, obtaining quantitative descriptions of geochemical patterns and identifying geochemical anomalies are important. To identify and separate geochemical anomalies, several statistical methodologies (nonstructural and structural) are presented by researchers. In this study, four nonstructural methods including threshold assessment method based on median and standard deviation, median absolute deviation (MAD), P.N product and Sinclair’s method are selected first and then U-statistic is considered as a structural method to compare their performance. Subsequently, the best method is used to assess prospective areas of Parkam district. Results show that P.N and Sinclair’s methods are not always efficient. MAD method reduced the background well and roughly increased the correlation factor of points. However, U-statistic method includes both mentioned advantages meaning in addition to reducing outlier data effect, it regularizes anomalous values and also their dispersion is reduced significantly. It is possible to determine anomaly areas according to anomalous samples positioning so that denser areas are more important. Finally, lithogeochemical map of study area is generated for copper and molybdenum. In this map, the Cu mineralization which is delineated by this method is closely associated with the defined potassic alteration zone (according to alteration map of the study area), and also, the delineated Mo mineralization is exactly associated with the phyllic alteration and is spatially conformable with the zone defined for it.
Similar content being viewed by others
References
Aral H, Sarac C (1988) Partitioning geochemical populations by Sinclair’s method. Commun Fac Sci Univ Ank Ser C 6:313–323
Berberian M, King GC (1981) Towards a paleogeography and tectonic evolution of Iran. Can J Earth Sci 18:210–265
Cheng Q (1999) Spatial and scaling modelling for geochemical anomaly separation. J Geochem Explor 65(3):175–194
Cheng Q, Agterberg FP, Ballantyne SB (1994) The separation of geochemical anomalies from background by fractal methods. J Geochem Explor 51:109–130
Cheng Q, Agterberg FP, Bonham-Carter GF (1996) A spatial analysis method for geochemical anomaly separation. J Geochem Explor 56:183–195
Cheng Q, Bonham-Carter GF, Hall GEM, Bajc A (1997) Statistical study of trace elements in the soluble organic and amorphous Fe–Mn phases of surficial sediments, Sudbury Basin. 1. Multivariate and spatial analysis. J Geochem Explor 59:27–64
Darabi-Golestan F, Ghavami-Riabi R, Khalokakaie R, Asadi-Haroni H, Seyedrahimi-Nyaragh M (2013) Interpretation of lithogeochemical and geophysical data to identify the buried mineralized area in Cu-Au porphyry of Dalli-Northern Hill. Arab J Geosci 6(11):4499–4509
Gent M, Menendez M, Toraño J, Torno S (2011) A review of indicator minerals and sample processing methods for geochemical exploration. J Geochem Explor 110(2):47–60
Ghannadpour SS (2013) Geochemical studies of porphyry copper ore deposit of Parkam, Tehran. MS Thesis, Amirkabir University of Technology
Ghannadpour SS, Hezarkhani A (2012) A developed software to calculate the additive constant number of average in three-variable normal logarithm. Glob J Comput Sci 2(1):1–6
Ghannadpour SS, Hezarkhani A (2014) Investigation of Cu, Mo, Pb, and Zn geochemical behavior and geological interpretations for Parkam porphyry copper system, Kerman, Iran. Arab J Geosci. doi:10.1007/s12517-014-1732-0
Ghannadpour SS, Hezarkhani A (2015) Exploration geochemistry data-application for anomaly separation based on discriminant function analysis in the Parkam porphyry system (Iran). Geosci J (accepted)
Ghannadpour SS, Hezarkhani A, Eshqi H (2012) Average and variance estimation programming in normal logarithmic distribution. Glob J Comput Sci 2(1):7–13
Ghannadpour SS, Mokhtari AR, Hezarkhani A, Fathianpour N (2013) Modification of Sinclair’s mixed statistical populations algorithm based on probability plots. J Anal Numer Method Min Eng 3(5):28–37 (in Persian with English abstract)
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 8:345–355
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. doi:10.1007/s12303-014-0064-0
Ghavami-Riabi R, Seyedrahimi-Niaraq MM, Khalokakaie R, Hazareh MR (2010) U-spatial statistic data modeled on a probability diagram for investigation of mineralization phases and exploration of shear zone gold deposits. J Geochem Explor 104(1):27–33
Gonçalves MA, Mateus A, Oliveira V (2001) Geochemical anomaly separation by multifractal modeling. J Geochem Explor 72(2):91–114
Hawkes HE, Webb JS (1962) Geochemistry in mineral exploration. Harper and Row, New York 415 p
Hezarkhani A (2006a) Mineralogy and fluid inclusion investigations in the Reagan Porphyry System, Iran, the path to an uneconomic porphyry copper deposit. J Asian Earth Sci 27(5):598–612
Hezarkhani A (2006b) Petrology of the intrusive rocks within the Sungun porphyry copper deposit, Azerbaijan, Iran. J Asian Earth Sci 27(3):326–340
Hezarkhani A, Ghannadpour SS (2015) Exploration information analysis, first edn. Amirkabir University of Technology (Tehran Polytechnic) press, Tehran (in Persian with English abstract)
Jébrak M (2006) Economic geology: then and now. Geosci Can 33(2):81–93
Lepeltier C (1969) A simplified statistical treatment of geochemical data by graphical representation. Econ Geol 64:538–550
Sinclair AJ (1976) Application of probability graphs in mineral exploration. The Association of Exploration Geichemistry, Special vol 4, 95 p
Sinclair AJ (1991) A fundamental approach to threshold estimation in exploration geochemistry: probability plots revisited. J Geochem Explor 41(1):1–22
Tangestani MH, Moore F (2001) Porphyry copper potential mapping using the weights-of-evidence model in a GIS, northern Shahr-e-Babak, Iran. Aust J Earth Sci 48(5):695–701
Xu L, Bi X, Hu R (2012) Relationships between porphyry Cu–Mo mineralization in the Jinshajiang–Red River metallogenic belt and tectonic activity: constraints from zircon U–Pb and molybdenite Re–Os geochronology. Ore Geol Rev 48:460–473
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Ghannadpour, S.S., Hezarkhani, A. Comparing U-statistic and nonstructural methods for separating anomaly and generating geochemical anomaly maps of Cu and Mo in Parkam district, Kerman, Iran. Carbonates Evaporites 32, 155–166 (2017). https://doi.org/10.1007/s13146-015-0282-1
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13146-015-0282-1