Skip to main content
SpringerLink
Log in

Typification of Gold Deposits for Evaluation and Exploration Purposes

  • Published:
Moscow University Geology Bulletin Aims and scope Submit manuscript

Abstract

The issues of selecting the parameters of an exploration grid based on quantitative criteria of the degree of exploration such as the accuracy of estimation of the average grades and the error in geometrization are considered. The admissible C1 category reserves are established based on the results of the analysis of actual data. The typification of gold deposits is based on an assessment of the scale of deposits, their morphology, and fractal dimension. An assessment of the variability of the gold grade in samples or composites is also used. To assess errors in geometrization at the early stages of geological exploration, a method for their determination based on the fractal geometry and geostatistical data is proposed.

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.

Similar content being viewed by others

REFERENCES

  1. Abzalov, M., Applied Mining Geology, Springer Int. Publ. Switzerland, 2016.

    Book  Google Scholar 

  2. Aleksandrova, A.E. and Kulikov, D.A., Methods of classification of reserves abroad, Nedropol’zovanie XXI Vek, 2019, no. 2, pp. 34–42.

  3. Australasian Code for Reporting of Exploration Results, Mineral Resources and Ore Reserves. The JORC Code 2012 Edition. Prepared by the Joint Ore Reserves Committee of the Australasian Institute of Mining and Metallurgy, Australian Inst. Geosci. Minerals Council of Australia (JORC), 2012.

  4. Coombs, J., The Art and Science of Resource Estimation. A Practical Guide for Geologists and Engineers, Australia, Pert, 2008.

    Google Scholar 

  5. David, M., Geostatistical Ore Reserve Estimation, Amsterdam, 1977.

    Google Scholar 

  6. Goryainov, P.M. and Ivanyuk, G.Yu., Samoorganizatsiya mineral’nykh system (Self-Organization in Mineral Systems), Moscow: GEOS, 2001.

  7. Iudin, D.I. and Kolosov, E.V., Fraktaly: ot prostogo k slozhnomu (Fractals: From Simple to Complex), Nizhny Novgorod: NNGASU, 2012.

  8. Ivanov, S.N. and Kushnarev, P.I., Assessment of exploration maturity of solid mineral reserves, Nedropol’zovanie XXI vek, 2019, no. 2 (78), pp. 82–92.

  9. Ivanov, S.N. and Kushnarev, P.I., Fractal geometry in solving problems of exploration and evaluation of solid mineral deposits, Razved. Okhr. Nedr, 2021, no. 2, pp. 32–38.

  10. Kazhdan, A.B., Metodologicheskie osnovy razvedki poleznykh iskopaemykh (Methodological Bases of Mineral Exploration), Moscow: Nedra, 1974.

  11. Klassifikatsiya zapasov i prognoznykh resursov tverdykh poleznykh iskopaemykh (Classification of Reserves and Forecast Resources of Solid Minerals), Moscow: MPR, 2006.

  12. Kotkin, V.A., Malukhin, G.N., Mel’nikova, A.V., et al., The quantitative assessment of the accuracy and reliability of the reserve resources of solid mineral deposits, Nedropol’zovanie XXI Vek, 2009, no. 1, pp. 29–33.

  13. Kushnarev, P.I., Substantiation of exploration grid geometry and reserves qualification (by the example of gold fields), Nedropol’zovanie XXI Vek, 2019, no. 5, pp. 32–37.

  14. Kushnarev, P.I., Analysis of the error in estimating the reserves of gold deposits, Razved. Okhr. Nedr, 2021, no. 4, pp. 25–30.

  15. Kushnarev, P.I. and Lazarev, A.B., Objects for estimation of the complexity of the geological structure of solid minerals deposits, Razved. Okhr. Nedr, 2021, no. 5, pp. 28–32.

  16. Kushnarev, P.I., Sytenkov, V.N., and Chicherina, A.G., Application of fractal geometry methods for assessing losses and ore dilution in the development of structurally complex deposits, Ratsional. Osvoenie Nedr, 2020, no. 5, pp. 64–72.

  17. Metodicheskie rekomendatsii po primeneniyu klassifikatsii zapasov mestorozhdenii i prognoznykh resursov tverdykh poleznykh iskopaemykh. Zoloto rudnoe (Guidelines for the Application of the Classification of Reserves of Deposits and Forecast Resources of Solid Minerals. Gold Ore), Moscow: GKZ, 2007.

  18. Usikov, Yu.T., Dostovernost’ geologicheskoi razvedochnoi informatsii (Reliability of Geological Exploration Data), Moscow: Nedra, 1988.

  19. Venttsel’, E.S., Teoriya veroyatnostei (Probability Theory), Moscow: Nauka, 1964.

  20. Vikent’ev, V.A., Vorontsov, V.A., Kushnarev, P.I., and Yaskovskii, P.P., On the properties of errors in geometrization, Izv. Vyssh. Uchebn. Razved., Geol. Razved., 1979, no. 2, pp. 96–107.

Download references

Author information

Authors and Affiliations

  1. All-Russian Scientific-Research Institute of Mineral Resources named after N.M. Fedorovsky, 119017, Moscow, Russia

    P. I. Kushnarev

  2. Moscow State University, 119991, Moscow, Russia

    A. A. Samsonov

Authors
  1. P. I. Kushnarev
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. A. Samsonov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to P. I. Kushnarev or A. A. Samsonov.

Ethics declarations

The authors declare that they have no conflicts of interest.

Additional information

Translated by D. Voroshchuk

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kushnarev, P.I., Samsonov, A.A. Typification of Gold Deposits for Evaluation and Exploration Purposes. Moscow Univ. Geol. Bull. 77, 489–496 (2022). https://doi.org/10.3103/S0145875222050088

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S0145875222050088

Keywords:

Search

Navigation