Skip to main content
Log in

The effects of mineralization on the lognormal distribution and exponential fluctuations of a hydrothermal gold deposit in Jiaodong Peninsula, China

  • Original Paper
  • Published:
Arabian Journal of Geosciences Aims and scope Submit manuscript

Abstract

Statistical analysis of the mineralization intensity in the No. І ore body of the Xincheng gold deposit in Jiaodong Peninsula, China, including grade and linear productivity, was used to study the mineralization characteristics of the hydrothermal gold deposit based on a lognormal distribution pattern and exponential fluctuations. The results show that the mineralization intensity of the hydrothermal gold deposit follows a lognormal distribution pattern. The grade and linear productivity in terms of the strike, dip, and thickness aspects are not linear, while the mineralization intensity fluctuations in exponential function were introduced between the peaks and valleys. This means the gold deposition mineralization process in the hydrothermal gold deposit takes place in accord with the mass action law of the first-order chemical reaction. The logarithmic averaging method is proposed to calculate the average grade and linear productivity of hypothermal gold deposits in accordance with the law of mineral fluctuations that are expressed as exponential functions. These research results have both academic and practical significance for further studies on hydrothermal gold mineralization, extra high-grade processing, improving traditional methods of estimation, and ultimately utilization of gold mineral reserves.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  • Bastante FG, Ordóñez C, Taboada J, Matías JM (2008) Comparison of indicator kriging, conditional indicator simulation and multiple-point statistics used to model slate deposits. Eng Geol 98(1):50–59. https://doi.org/10.1016/j.enggeo.2008.01.006

    Article  Google Scholar 

  • Bayirli M (2014) Numerical approaches of cluster statistics for stochastic manganese deposits. Zeitschrift Fur Naturforschung A 69(10–11):581–588. https://doi.org/10.5560/ZNA.2014-0054

    Article  Google Scholar 

  • Chen YJ, Pirajno F, Lai Y et al (2004) Metallogenic time and tectonic setting of the Jiaodong gold province, eastern China. Acta Petrol Sin 20(4):907–922

    Google Scholar 

  • Chen YJ, Pirajno F, Qi JP (2005) Origin of gold Metallogeny and sources of ore-forming fluids, Jiaodong Province, eastern China. Int Geol Rev 47(5):530–549. https://doi.org/10.2747/0020-6814.47.5.530

    Article  Google Scholar 

  • Clay AN, Myburgh JA, Orford TC et al (2011) Using simple statistics to define confidence limits for reliable quantitative definition of mineral resources—the Venmyn Variance Tower. J South Afr Inst Min Metall 112(112):985–992

    Google Scholar 

  • Dag A, Mert BA (2008) Evaluating thickness of bauxite deposit using indicator geostatistics and fuzzy estimation. Resour Geol 58(2):188–195. https://doi.org/10.1111/j.1751-3928.2008.00055.x

    Article  Google Scholar 

  • David M (1977) Geostatistical ore reserve estimation. Elsevier Scientific Publishing Company, New York

    Google Scholar 

  • 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. https://doi.org/10.1016/j.gexplo.2009.10.002

    Article  Google Scholar 

  • Goovaerts P (1997) Geostatistics for natural resource evaluation. Oxford University Press, New York

    Google Scholar 

  • Grijp YVD, Minnitt RCA (2015) Application of direct sampling multi-point statistic and sequential Gaussian simulation algorithms for modelling uncertainty in gold deposits. J South Afr Inst Min Metall 115(1):73–85. https://doi.org/10.17159/2411-9717/2015/v115n1a8

    Article  Google Scholar 

  • Guilbert JM, Park CF (2007) The geology of ore deposits. Waveland Press, Illinois

    Google Scholar 

  • Journel AG, Huijbregts CJ (1978) Mining geostatistics. Academic Press, New York

    Google Scholar 

  • Juran JM, Godfrey AB (1999) Juran’s quality handbook. McGraw-Hill Professional, New York

    Google Scholar 

  • Krige DG (1953) A statistical approach to some basic mine valuation problems on the Witwatersrand. J Chem Metall Min Soc S Afr 52(6):119–139. https://doi.org/10.2307/3006914

    Article  Google Scholar 

  • Li JW, Vasconcelos PM, Zhang J, Zhou MF, Zhang XJ, Yang FH (2003) Ar-40/Ar-39 constraints on a temporal link between gold mineralization, magmatism, and continental margin transtension in the Jiaodong gold province, Eastern China. J Geol 111(6):741–751. https://doi.org/10.1086/378486

    Article  Google Scholar 

  • Lin JF, Chen RH, Li D et al (2011) A new method of recognition and processing extra-high-grade value. Min Metall 20(3):36–41

    Google Scholar 

  • Liu W (2007) Research on the geochemical feature, genesis and metallogenic prognosis in the ShiHu gold deposit. Central South University, Western Hebei Province

    Google Scholar 

  • Lv GX, Guo T, Shu B et al (2007) Study on the multi-level controlling rule for tectonic system in Jiaodong gold-centralized area. Geotecton Metallog 31(2):193–204

    Google Scholar 

  • Lv GX, Wu GG, Chen XL et al (2011) Structural and geochemical characteristics of alteration zone of Xincheng gold deposit. Geotecton Metallog 35(4):618–627

    Google Scholar 

  • Mao JW, Wang YT, Li HM, Pirajno F, Zhang C, Wang R (2008) The relationship of mantle-derived fluids to gold metallogenesis in the Jiaodong Peninsula: evidence from D-O-C-S isotope systematic. Ore Geol Rev 33(3):361–381. https://doi.org/10.1016/j.oregeorev.2007.01.003

    Article  Google Scholar 

  • Mao Z, Lai J, Bo Y (2014) The geochemical multi-fractal characteristics and mineralization of the Dehelongwa copper-gold deposit. Chin J Geochem 33(3):280–288. https://doi.org/10.1007/s11631-014-0689-8

    Article  Google Scholar 

  • Matheron G (1962) Traité de géostatistique appliquée. Éditions Technip, Paris

    Google Scholar 

  • Matheron G (1963) Principles of geostatistics. Econ Geol 58(8):1246–1266

    Article  Google Scholar 

  • Miao SJ, Li Y, Tan WH, Ren F (2012) Relation between the in-situ stress field and geological tectonics of a gold mine area in Jiaodong Peninsula, China. Int J Rock Mech Min Sci 51(4):76–80. https://doi.org/10.1016/j.ijrmms.2012.01.007

    Article  Google Scholar 

  • Sarama DD (2009) Geostatistics with applications in earth sciences, Second edn. Capital Publishing Company, New Delhi

    Book  Google Scholar 

  • Tripp GI, Vearncombe JR (2004) Fault/fracture density and mineralization: a contouring method for targeting in gold exploration. J Struct Geol 26(6):1087–1108. https://doi.org/10.1016/j.jsg.2003.11.002

    Article  Google Scholar 

  • Voroshilov VG (2009) Anomalous structures of geochemical fields of hydrothermal gold deposits: formation mechanism, methods of geometrization, typical models, and forecasting of ore mineralization. Geol Ore Deposits 51(1):1–16. https://doi.org/10.1134/S1075701509010012

    Article  Google Scholar 

  • Wang ZL (2012) Metallogenic system of Jiaojia Gold Orefield, Shandong Province, China. China University of Geosciences, Beijing

    Google Scholar 

  • Wang G, Pang Z, Boisvert JB, 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). J Geochem Explor 134(11):85–98. https://doi.org/10.1016/j.gexplo.2013.08.004

    Article  Google Scholar 

  • Wang H, Cheng Q, Zuo R (2015) Spatial characteristics of geochemical patterns related to Fe mineralization in the southwestern Fujian province (China). J Geochem Explor 148:259–269. https://doi.org/10.1016/j.gexplo.2014.10.010

    Article  Google Scholar 

  • Xia L (2003) Tectonic physicochemistry study on regional fluid in East Shandong area during Mesozoic gold mineralization. Chinese Academy of Geological Sciences, Beijing

    Google Scholar 

  • Yan FZ, Li QZ (2008) Yanshan gold deposit: the largest Carlin and Carlin-like type gold deposit in China. Acta Geol Sin 82(4):804–810. https://doi.org/10.1111/j.1755-6724.2008.tb00634.x

    Article  Google Scholar 

  • Zhang J (1991) On temporal structure features of gold mineralization in Zhaoyuan-Yexian region. Earth Sci 16(4):403–410

    Google Scholar 

  • Zhu YS (2007) Geological characteristics and metallogenic lineage of the main metallogenic regions in China. Geology Publishing House, Beijing

    Google Scholar 

Download references

Acknowledgements

Thanks to Shandong Provincial Bureau of Geology & Mineral Resources and Xincheng Gold Mine for providing a great number of geological data, carrying out supplementary exploration and Au content analysis for the research.

Funding

This work was supported by the National Key Basic Research Program of China (973 Program) (No. 2015CB060200), and National Natural Science Foundation of China (No. 51574014, No. 51534002, and No. 41772168).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shengjun Miao.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Miao, S., Wang, H., Guo, X. et al. The effects of mineralization on the lognormal distribution and exponential fluctuations of a hydrothermal gold deposit in Jiaodong Peninsula, China. Arab J Geosci 11, 529 (2018). https://doi.org/10.1007/s12517-018-3898-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12517-018-3898-3

Keywords

Navigation