Arabian Journal of Geosciences

, 11:529 | Cite as

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

  • Shengjun MiaoEmail author
  • Hui Wang
  • Xuelian Guo
  • Xiangyang Guo
  • Changqing Kong
Original Paper


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.


Hydrothermal gold deposit Mineralization intensity Lognormal distribution Fluctuations in exponential function 



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 information

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).


  1. 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. CrossRefGoogle Scholar
  2. Bayirli M (2014) Numerical approaches of cluster statistics for stochastic manganese deposits. Zeitschrift Fur Naturforschung A 69(10–11):581–588. CrossRefGoogle Scholar
  3. 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):907–922Google Scholar
  4. 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. CrossRefGoogle Scholar
  5. 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):985–992Google Scholar
  6. Dag A, Mert BA (2008) Evaluating thickness of bauxite deposit using indicator geostatistics and fuzzy estimation. Resour Geol 58(2):188–195. CrossRefGoogle Scholar
  7. David M (1977) Geostatistical ore reserve estimation. Elsevier Scientific Publishing Company, New YorkGoogle Scholar
  8. 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. CrossRefGoogle Scholar
  9. Goovaerts P (1997) Geostatistics for natural resource evaluation. Oxford University Press, New YorkGoogle Scholar
  10. 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. CrossRefGoogle Scholar
  11. Guilbert JM, Park CF (2007) The geology of ore deposits. Waveland Press, IllinoisGoogle Scholar
  12. Journel AG, Huijbregts CJ (1978) Mining geostatistics. Academic Press, New YorkGoogle Scholar
  13. Juran JM, Godfrey AB (1999) Juran’s quality handbook. McGraw-Hill Professional, New YorkGoogle Scholar
  14. 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. CrossRefGoogle Scholar
  15. 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. CrossRefGoogle Scholar
  16. Lin JF, Chen RH, Li D et al (2011) A new method of recognition and processing extra-high-grade value. Min Metall 20(3):36–41Google Scholar
  17. Liu W (2007) Research on the geochemical feature, genesis and metallogenic prognosis in the ShiHu gold deposit. Central South University, Western Hebei ProvinceGoogle Scholar
  18. 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):193–204Google Scholar
  19. Lv GX, Wu GG, Chen XL et al (2011) Structural and geochemical characteristics of alteration zone of Xincheng gold deposit. Geotecton Metallog 35(4):618–627Google Scholar
  20. 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. CrossRefGoogle Scholar
  21. 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. CrossRefGoogle Scholar
  22. Matheron G (1962) Traité de géostatistique appliquée. Éditions Technip, ParisGoogle Scholar
  23. Matheron G (1963) Principles of geostatistics. Econ Geol 58(8):1246–1266CrossRefGoogle Scholar
  24. 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. CrossRefGoogle Scholar
  25. Sarama DD (2009) Geostatistics with applications in earth sciences, Second edn. Capital Publishing Company, New DelhiCrossRefGoogle Scholar
  26. 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. CrossRefGoogle Scholar
  27. 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. CrossRefGoogle Scholar
  28. Wang ZL (2012) Metallogenic system of Jiaojia Gold Orefield, Shandong Province, China. China University of Geosciences, BeijingGoogle Scholar
  29. 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. CrossRefGoogle Scholar
  30. 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. CrossRefGoogle Scholar
  31. Xia L (2003) Tectonic physicochemistry study on regional fluid in East Shandong area during Mesozoic gold mineralization. Chinese Academy of Geological Sciences, BeijingGoogle Scholar
  32. 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. CrossRefGoogle Scholar
  33. Zhang J (1991) On temporal structure features of gold mineralization in Zhaoyuan-Yexian region. Earth Sci 16(4):403–410Google Scholar
  34. Zhu YS (2007) Geological characteristics and metallogenic lineage of the main metallogenic regions in China. Geology Publishing House, BeijingGoogle Scholar

Copyright information

© Saudi Society for Geosciences 2018

Authors and Affiliations

  1. 1.Department of Civil EngineeringUniversity of Science and Technology BeijingBeijingChina
  2. 2.Beijing Key Laboratory of Urban Underground Space EngineeringUniversity of Science and Technology BeijingBeijingChina
  3. 3.School of Earth Sciences, Key Laboratory of Western China’s Mineral Resources of Gansu ProvinceLanzhou UniversityLanzhouChina

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