Journals →  Gornyi Zhurnal →  2024 →  #3 →  Back

MINING PROCESSES
ArticleName Application of microseismic monitoring data in prediction of stoping influence zone size: A case-study of Oktyabrsky Mine
DOI 10.17580/gzh.2024.03.05
ArticleAuthor Marysyuk V. P., Trofimov A. V., Andreev A. A., Kolganov A. V.
ArticleAuthorData

NorNickel’s Polar Division, Norilsk, Russia

V. P. Marysyuk, Chief Geotechnical Engineer—Director, Center for Geodynamic Safety, Candidate of Engineering Sciences

 

Geotechnique Laboratory, Gipronickel Institute, Saint-Petersburg, Russia
A. V. Trofimov, Head, Candidate of Engineering Sciences, trofimovav@nornik.ru

 

Empress Catherine II Saint-Petersburg Mining University, Saint-Petersburg, Russia
A. A. Andreev, Head of Projects of Research Center for Geomechanics and Mining Practice Problems
A. V. Kolganov, Post-Graduate Student

Abstract

The problem connected with the determination of size of a stoping influence zone is highly relevant in mining if operating safety depends on integrity of overlying rock mass. For mining operations under water-bearing objects, where integrity of the impermeable strata is a key safety factor, as well as when ore bodies occur in the close vicinity to the ground infrastructure facilities and it is necessary to ensure safety of buildings and structures, the mentioned issue is also burning. There is an ample experience accumulated in the field of the influence zone size determination in coal mining with compete caving of mined-out space using the finite and discrete element methods and the empirical approaches. However, in the conditions of Oktyabrsky Mine, which uses the cut-and-backfill method, predictions based on the approaches and experience gained in the other geological conditions may yield irrational results. As an alternative for the prediction of the stoping influence zone size in Oktyabrsky Mine, the calculation method using the data of regional rockburst hazard prediction by microseismic monitoring is implemented, and the most representative characteristics of seismic activity above a mined-out area of cupriferous iron ore strata are selected. Using these data, the relationship of the stoping influence zone size and the ore body thickness is obtained.
The authors appreciate participation of E. V. Rodionova and M. V. Tereshchenko, staff members of NorNickel’s Polar Division in this study.

keywords Microseismic monitoring, fracturing, stoping influence zone, interpolation, geostatistics, kriging, minimum curvature method, Gaussian model
References

1. Gospodarikov A.P., Trofimov A.V., Kirkin A.P. Evaluation of deformation characteristics of brittle rocks beyond the limit of strength in the mode of uniaxial servohydraulic loading. Journal of Mining Institute. 2022. Vol. 256. pp. 539–548.
2. Galchenko Yu. P., Eremenko V. A. Evolution of secondary stress field during underground mining of thick ore bodies. Eurasian Mining. 2021. No. 1. pp. 21–24.
3. Zuev B. Yu., Zubov V. P., Fedorov A. S. Application prospects for models of equivalent materials in studies of geomechanical processes in underground mining of solid minerals. Eurasian Mining. 2019. No. 1. pp. 8–12.
4. Shabarov A. N., Kuranov A. D., Kiselev V. A. Assessing the zones of tectonic fault influence on dynamic rock pressure manifestation at Khibiny deposits of apatite-nepheline ores. Eurasian Mining. 2021. No. 2. pp. 3–7.
5. Saadoun A., Fredj M., Boukarm R., Hadji R. Fragmentation analysis using digital image processing and empirical model (KuzRam): a comparative study. Journal of Mining Institute. 2022. Vol. 257. pp. 822–832.
6. Zhang C., Mitra R., Oh J., Hebblewhite B. Analysis of mining-induced valley closure movements. Rock Mechanics and Rock Engineering. 2016. Vol. 49, Iss. 5. pp. 1923–1941.
7. Khanal M., Qu Q., Zhu Y., Xie J., Zhu W. et al. Characterization of overburden deformation and subsidence behavior in a kilometer deep longwall mine. Minerals. 2022. Vol. 12, Iss. 5. ID 543.
8. Liu Y., Cheng J., Jiao J., Meng X. Feasibility study on multi-seam upward mining of multi-layer soft–hard alternate complex roof. Environmental Earth Sciences. 2022. Vol. 81, Iss. 17. ID 424.
9. Guo W., Mishra B., Zhao G., Bai E. Critical failure criteria of the overlying rock strata due to high-intensity longwall coal mining in China. Proceedings of the 38th International Conference on Ground Control in Mining. Englewood : Society for Mining, Metallurgy, and Exploration, 2019. pp. 311–318.
10. Li J., Li B., Gao Y., Cui F., He K. et al. Mechanism of overlying strata migration and failure during underground mining in the mountainous carbonate areas in southwestern China. Frontiers in Earth Science. 2022. Vol. 10. ID 874623.
11. Wang F., Tu S., Zhang C., Zhang Y., Bai Q. Evolution mechanism of water-flowing zones and control technology for lon gwall mining in shallow coal seams beneath gully topography. Environmental Earth Sciences. 2016. Vol. 75, Iss. 19. ID 1309.
12. Zhang W., Li B., Zhang G., Li Z. Investigation of water-flow fracture zone height in fully mechanized cave mining beneath thick alluvium. Geotechnical and Geological Engineering. 2017. Vol. 35, Iss. 4. pp. 1745–1753.
13. Tan Y., Cheng H., Lv W., Yan W., Guo W. et al. Calculation of the height of the waterconducting fracture zone based on the analysis of critical fracturing of overlying strata. Sustainability. 2022. Vol. 14, Iss. 9. ID 5221.
14. Gendler S. G., Kryukova M. S. Thermal management of metro lines, including doubletrack and single-track tunnels. MIAB. 2023. No. 9-1. pp. 248–269.
15. Aynbinder I. I., Kaplunov D. R. Risk-based approach to selection of deep-level mining technology. MIAB. 2019. No. 4. pp. 5–19.
16. Tan Y., Xu H., Yan W., Guo W., Sun Q. et al. Development law of water-conducting fracture zone in the fully mechanized caving face of gob-side entry driving: A case study. Minerals. 2022. Vol. 12, Iss. 5. ID 5 57.
17. Liu C., Li H., Mitri H. Effect of stra ta conditions o n shield pressure and surface subsidence at a longwall top coal caving working face. Rock Mechanics and Rock Engineering. 2019. Vol. 52, Iss. 5. pp. 1523–1537.
18. Wesseloo J., Cumming-Potvin D., Potvin Y., Jacobsz S. W., Kearsley E. Physical modelling to provide data-rich case studies for the verification and validation of numerical modelling predictions of cave mechanics problems. MassMin 2020 : Proceedings of the Eighth International Conference & Exhibition on Mass Mining. Santiago : University of Chile, 2020. pp. 462–477.
19. Tabois G. Q., Salas J. D. A comparative analysis of techniques for spatial interpolation of precipitation. Water Resources Bulletin. 1985. Vol. 21, No. 3. pp. 365–380.
20. Weber D., Englund E. Evaluation and comparison of spatial interpolators. Mathematical Geology. 1992. Vol. 24, No. 4. pp. 381–391.
21. Armstrong M. Common problems seen in variograms. Mathematical Geology. 1984. Vol. 16, No. 3. pp. 305–313.
22. Kanevskiy M., Demyanov V., Saveleva E. et al. Basic Introduction to Geostatistics. Series : Environment and Natural Wealth. Moscow : VINITI, 1999. No. 11. 136 p.
23. Matheron G. Traité de géostatistique appliquée. Tome 1, 2. Paris : Éditions Technip, 1963. 506 p.
24. Kanevski M. (Ed.). Advanced Mapping of Environmental Data: Geostatistics, Machine Learning and Bayesian Maximum Entropy. London : ISTE, 2008. 352 p.
25. Christakos G. Modern Spatiotemporal Geostatistics. Oxford : Oxford University Press, 2000. 289 p.

Language of full-text russian
Full content Buy
Back