Forecasting stability of Irokinda deposit underground mine workings based on comparison of rock mass state prediction estimate methods

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The purpose of the study is to compare and adjust the results of stability forecast for Irokinda gold deposit underground mine workings using various estimation methods of rock mass state based on the analysis of structural parameters only, multiparameter classification of structural parameters and engineering-geological indicators according to Z. Bieniawski as well as mass fracturing distribution. Engineering and geological conditions of deposit deep horizons have been estimated using the data obtained under geomechanical description of the core when drilling exploratory and hydrogeological boreholes and description of the walls of underground mine workings. All these made it possible to estimate the rock mass fragmentation degree, which affects the stability of underground mine workings. A full range of physical, mechanical and deformation property definition was performed using rock samples taken from the core of exploratory boreholes and mine workings. A total of 184 samples have been taken and analyzed during the field season with distinguishing of 10 rock varieties characterized by different strength and stability degree. The comparative analysis conducted on the example of the Irokinda field implies the need of the integrated use of these methods, which will enable increasing of result reliability and most accurate determination of the stability class of the rock mass for its further mining. The results obtained by various methods should be considered as a set of signals for making design decisions on strengthening mine workings.

About the authors

I. V. Matveeva

Irkutsk National Research Technical University

Email: matveeva.i.2010@mail.ru
ORCID iD: 0009-0000-8621-5560

T. O. Shigarova

Irkutsk National Research Technical University

Email: shigarova@yandex.ru
ORCID iD: 0009-0008-5305-0251

O. A. Matveev

Irkutsk National Research Technical University

Email: matveev_oleg68@mail.ru
ORCID iD: 0009-0006-8053-0782

References

  1. Кузьмин Е.В., Узбекова А.Р. Рейтинговые классификации массивов скальных пород: предпосылки создания, развитие и область применения // Горный информационно-аналитический бюллетень. 2004. № 4. С. 201–202. EDN: INTNKV.
  2. Кузьмин Е.В., Узбекова А.Р. Самообрушение руды при подземной добыче. М.: Изд-во МГГУ, 2006. 283 с.
  3. Абрамкин Н.И., Ефимов В.И., Мансуров П.А. Эмпирические методики оценки состояния массива горных пород // Известия уральского государственного горного университета. 2021. № 4. С. 109–115. https://doi.org/10.21440/2307-2091-2021-4-109-115. EDN: ELNONZ.
  4. Чернов А.Ю., Бузов С.А. Применение рейтинговых классификаций массивов горных пород на основе общепринятой системы документации горных выработок // Сергеевские чтения: материалы годичной сессии Научного совета РАН по проблемам геоэкологии, инженерной геологии и гидрогеологии (г. Пермь, 2–4 апреля 2019). Пермь: Изд-во ПГНИУ, 2019. С. 603–608. EDN: ZCOYLR.
  5. Deere D.U., Deere D.W. The Rock quality designation (RQD) index in practice // Rock Classification Systems for Engineering Purposes / ed. L. Kirkaldie. West Conshohocken: ASTM International, 1988. P. 91–101. https://doi.org/10.1520/STP48465S.
  6. Terzaghi R.D. Sources of error in joint surveys // Geotechnique. 2009. Vol. 15. Iss. 3. P. 287–304. https://doi.org/10.1680/geot.1965.15.3.287.
  7. Barton N., Lien R., Lunde J. Engineering classification of rock masses for the design of rock support // Rock Mechanics and Rock Engineering. 1974. Vol. 6. Iss. 4. P. 189–236. https://doi.org/10.1007/BF01239496.
  8. Haines A., Terbrugge P., Carrieri G. Preliminary estimation of rock slope stability using rock mass classification systems // Proc. 7th Cong. on Rock Mechanics (Aachen, 16–20 September 1991). Aachen: A.A. Balkema, 1991. Vol. 2. P. 887–892. https://doi.org/10.1016/0148-9062(93)92931-F.
  9. Bieniawski Z.T. Engineering rock mass classifications. New York: John Willey and Sons, 1989. 251 p.
  10. Romana M. New adjustment rating for application of the Bieniawski classifications to slopes // Proceedings of International Symposium on the Role of Rock Mechanics (Zacatecas, 1985). Zacatecas: International Society of Rock Mechanics, 1985. P. 49–53.
  11. Кузьмин Е.В., Узбекова А.Р. Рейтинговые классификации массивов горных пород и их практическое применение // Горный информационно-аналитический бюллетень. 2005. № 5. С. 181–185. EDN: ICJNJN.
  12. Рыбин В.В., Губинский Н.О. Определение рейтинга массива горных пород по классификации Д. Лобшира для условий карьеров ОАО «Апатит» // Горный информационно-аналитический бюллетень. 2012. № 3. С. 140–143. EDN: PUXDSF.
  13. Laubsher D.H. A geomechanics classification system for rating of rock mass in mine design // Journal of the Southern African Institute of Mining and Metallurgy. 1990. Vol. 90. P. 257–273.
  14. Jacubec J., Laubscher D. The MRMR rock mass rating classification system in mining practice // MassMin (Brisbane, 29 October – 2 November 2000). Brisbane, 2000. P. 413–421.
  15. Laubscher D.H., Jacubec J. The MRMR Rock Mass Classification for jointed rock masses // Underground Mining Methods: Engineering Fundamentals and International Case Histories / eds. W.A. Hustrulid, R.L. Bullock. Littleton: SME, 2001. P. 455–463.
  16. Bieniawski Z.T. Determining rock mass deformability: experience from case histories // International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts. 1978. Vol. 15. Iss. 5. P. 237–247. https://doi.org/10.1016/0148-9062(78)90956-7.
  17. Nicholoson G.A., Bieniawski Z.T. A nonlinear deformation modulus based on rock mass classification // International Journal of Mining and Geological Engineering. 1990. Vol. 8. P. 181–202. https://doi.org/10.1007/BF01554041.
  18. Barton N. Some new Q-value correlations to assist in site characterization and tunnel design // International Journal of Rock Mechanics and Mining Sciences. 2002. Vol. 39. Iss. 2. P. 185–216. https:///doi.org/10.1016/S1365-1609(02)00011-4.

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