Regarding correlation between the ore grade and the state of natural and man-made rock masses

DOI: https://doi.org/10.30686/1609-9192-2026-3-137-141

Читать на русскоя языке V.I. Golik1, A.V. Titova2
1 Moscow Polytechnic University, Moscow, Russian Federation
2 Vernadsky State Geological Museum, Moscow, Russian Federation
Russian Mining Industry №3/ 2026 p. 137-141

Abstract: The article discusses topical issues of managing the condition of ore-bearing rocks to improve the environmental and economic performance of mining operations in the national economy. Methods of managing the state of the rock mass are summarized, systematized and analyzed, natural relationships and correlations between the ore grades are established, a forecast for improving the performance of operations is made, and recommendations on improving ore mining and processing methods are given. A model to determine the benefits from improving the ore grades and the results of its implementation options in the Mapl system with quantitative characteristics of the ratio between the cost of managing the rock mass and the cost of filling the worked-out space is formed. It is shown that an increase in the area of exposed rock and duration of the stoping operation scales up dilution, selective mining of high-grade ores makes the process of backfilling the worked-out space and raises the material costs. An algorithm is presented for extracting metals from ores of different grades, a scheme for combining traditional and innovative mining methods is developed, and information on the results of the combination is provided. A model with independent variables is proposed to determine the efficiency of combining the methods. Dependence diagrams of variable mining and processing factors for gold-bearing ores are given. It is concluded that the cost of managing the condition of the ore-bearing rock mass is an important factor in shaping the economic performance of operations, and the worked-out space is a three-dimensional probability distribution for which the volume of the mine workings and the rock properties are interdependent factors. The research results can be used in upgrading underground mining technologies, as well as in training of highly qualified personnel.

Keywords: rock mass, correlation, ore grade, ore mining method, mathematical model, metal extraction

For citation: Golik V.I., Titova A.V. Regarding correlation between the ore grade and the state of natural and man-made rock masses. Russian Mining Industry. 2026;(3):137–141. https://doi.org/10.30686/1609-9192-2026-3-137-141


Article info

Received: 16.02.2026

Revised: 24.03.2026

Accepted: 01.04.2026


Information about the authors

Vladimir I. Golik – Dr. Sci. (Eng.), Professor of the Department of Metallurgy, Moscow Polytechnic University, Moscow, Russian Federation; https://orcid.org/0000-0002-1181-8452; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Asya V. Titova – Dr. Sci. (Eng.), Vernadsky State Geological Museum of the Russian Academy of Sciences, Moscow, Russian Federation


References

1. Lyashenko V.I., Khomenko O.E., Golik V.I. Friendly and resource-saving methods of underground ore mining in disturbed rock masses. Mining Science and Technology (Russia). 2020;5(2):104–118. https://doi.org/10.17073/2500-0632-2020-2-104-118

2. Adero N.J., Drebenstedt C., Prokofeva E.N., Vostrikov A.V. Spatial data and technologies for geomonitoring of land use under aspect of mineral resource sector development. Eurasian Mining. 2020;(1):69–74. https://doi.org/10.17580/em.2020.01.14

3. Klyuev R.V., Bosikov I.I., Mayer A.V., Gavrina O.A. Comprehensive analysis of the effective technologies application to increase sustainable development of the natural-technical system. Sustainable Development of Mountain Territories. 2020;12(2):283–290. (In Russ.)

4. Kulikova E.Yu., Balovtsev S.V., Skopintseva O.V. Comprehensive assessment of geoecological risks in conducting open and underground mining. Sustainable Development of Mountain Territories. 2024;16(1):205–216. (In Russ.) https://doi.org/10.21177/1998-4502-2024-16-1-205-216

5. Khakulov V.A., Karamurzov B.S., Sytsevich N.F., Kononov O.V. Prospects of mining revitalization at Tyrnyauzsky deposit based on geotechnical mapping and reappraisal of remaining reserves. Gornyi Zhurnal. 2015;(8):13–18. (In Russ.) https://doi.org/10.17580/gzh.2015.08.03

6. de Saracibar C.A. Nonlinear continuum mechanics: An engineering approach. Cham: Springer; 2023. 344 p. https://doi.org/10.1007/978-3-031-15207-8

7. Klyuev R.V., Martyushev N.V., Kukartsev V.V., Kukartsev V.A., Brigida V. Analysis of geological information toward sustainable performance of geotechnical systems. Mining Informational and Analytical Bulletin. 2024;(5):144–157. (In Russ.) https://doi.org/10.25018/0236_1493_2024_5_0_144

8. Khomenko O.E., Lyashenko V.I. New technologies and technical means of fixing mine workings using geo-energy. Mine Surveying Bulletin. 2020;(4):54–61. (In Russ.)

9. Golik V.I., Komashchenko V.I., Kachurin N.M. Concept of combining technologies by mining ore deposits. Izvestiya Tulskogo Gosudarstvennogo Universiteta. Nauki o Zemle. 2015;(4):76–88. (In Russ.)

10. Sánchez F., Hartlieb P. Innovation in the mining industry: technological trends and a case study of the challenges of disruptive innovation. Mining, Metallurgy & Exploration. 2020;37(5):1385–1399. https://doi.org/10.1007/s42461-020-00262-1

11. Golik V.I., Titova A.V. Modelling of mining performance indicators for the Sadon ore deposits. Russian Mining Industry. 2022;(4):82–87. (In Russ.) https://doi.org/10.30686/1609-9192-2022-4-82-87

12. Zhang Y., Wu J., Liu M., Tan A. TSN-based routing and scheduling scheme for Industrial Internet of Things in underground mining. Engineering Applications of Artificial Intelligence. 2022;115:105314. https://doi.org/10.1016/j.engappai.2022.105314