Journal of Mining Science

, Volume 54, Issue 4, pp 535–540 | Cite as

Integrated Multi-Level Geomonitoring of Natural-and-Technical Objects in the Mining Industry

  • N. N. Mel’nikov
  • A. I. KalashnikEmail author
  • N. A. Kalashnik
  • D. V. Zaporozhets


The system of integrated multi-level geomonitoring is developed for technical objects and oil/gas reservoirs in the west of Russian Arctic. The system is based on the principle of synchronization of inter-branch researches, including geodetic, geomechanical, geophysical and geotechnical measurements on the ground surface and by GPS, as well as subsurface, surface, aerial and GPR survey. The system uses the information technologies Big Data and Cloud Service with intelligence elements, and provides geomonitoring investigations at differ levels: remote, air, surface, subsurface, computer. In-situ inter-branch multi-level studies are the framework of the geomonitoring which continuously replenish and updates data bases. The multi-level approach is also involved in computer modeling: the geodynamic models of a manmade object, Kola Peninsula, Baltic Shield and Eurasian Plate are created as hierarchically nested structures. The models are analyzed under various boundary conditions, which enabled solution of an inverse problem on stress state of subsurface rock mass differentially by the investigates scales. The multi-level geomonitoring system is implemented at technical objects of the key mining companies of the Kola Peninsula: Kovdorsky GOK, Kola MMC, Apatit, Oleniy Ruchey and OLKON GOKs.


Multi-level geomonitoring integrated inter-branch studies natural-and-technical objects mining industry 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Mel’nikov, N.N. and Kalashnik, A.I., Sozdanie mnogourovnevoi sistemy geodinamicheskogo geomonitoringa gornotekhnicheskikh i neftegazovykh ob’ektov zapadnoi chasti Rossiiskogo sektora Arktik (Creating a Multilevel System for Geodynamic Geomonitoring of Mining Aad Petroleum Production Sites in the Western Russian Arctic), Arktika: Ekologiya i Ekonomika, 2015, no. 3 (19), pp. 66–75.Google Scholar
  2. 2.
    Bychkov, I.V., Vladimirov, D N., Oparin, V.N., Potapov, V.P., and Shokin, Yu. I., Mining Information Science and Big Data Concept for Integrated Safety Geomonitoring and Subsoil Management, J. Min. Sci., 2016, vol. 52, no. 6, pp. 1195–1204.CrossRefGoogle Scholar
  3. 3.
    Hartwig, M. E., Detection of Mine Slope Motions in Brazil as Revealed by Satellite Radar Interferograms, Bulletin of Engineering Geology and the Environment, 2016, vol. 75, no. 2, pp. 605–621.CrossRefGoogle Scholar
  4. 4.
    Alabyan, A.M., Zelentsov, V.A., Krylenko, I.N., Potryasaev, S.A., Sokolov, B.V., and Yusupov, R.M., Design of Intelligent Information Systems for Real-Time Prediction of River Floods), Vestn. Ross. Akad. Nauk, 2016, vol. 86, no. 2, pp. 127–137Google Scholar
  5. 5.
    Jiang, H., Lin, P., Fan, Q., and Qiang, M., Real-Time Safety Risk Assessment Based on a Real-Time Location System for Hydropower Construction Sites, The Scientific World Journal, 2014, Article ID 235970, p. 14.Google Scholar
  6. 6.
    Mel’nikov, N.N., Kalashnik, A.I., Kalashnik, N.A., and Zaporozhets, D.V., Modern Methods for Comprehensive Studies of Waterworks in the Barents Sea Region), Vestn. MGTU, 2017, vol. 20, no. 1, pp. 13–20.CrossRefGoogle Scholar
  7. 7.
    Mel’nikov, N.N., Kalashnik, A.I., Zaporozhets, D.V., D’yakov, A. Yu., and Maksimov, D.A., Experience of Using GPR Surveys in the Western Russian Arctic), Probl. Arkt. Antarkt., 2016, no. 1, pp. 39–49.Google Scholar
  8. 8.
    Zelentsov, V.A., Kovalev, A.P., Okhtilev, M.Yu., Sokolov, B.V., and Yusupov, R.M., Methodology for Design and Use of Intelligent Information Technologies of Terrestrial-Spaceborne Geomonitoring of Complex Objects, SPIIRAN Transactions, 2013, no. 5 (28), pp. 7–81.Google Scholar
  9. 9.
    Kozhaev, Zh.T., Mukhamedgalieva, M.A., Imansakipova, B.B., and Mustafin, M.G. Geoinformation System for Geomechanical Monitoring of Ore Deposits Using Spaceborn Radar Interferometry, Gornyi Zhurnal, 2017, no. 2, pp. 39–44.Google Scholar
  10. 10.
    Mikhailov, V.O., Kiseleva, E.A., Smol’yaninova, E.I., Golubev, V.I., Dmitriev, P.N., Timoshkina, E.P., Different Methods for Radar Data Processing and Slope Stability Monitoring in the Great Sochi Area: Experience Summary), Sovr. Probl. Dist. Zond. Zemli iz Kosmosa, 2016, vol. 13, no. 6, pp. 137–147.CrossRefGoogle Scholar
  11. 11.
    Ferretti, A., Satellite InSAR Data: Reservoir Monitoring from Space, EAGE Publications bv, 2014.Google Scholar
  12. 12.
    Kalashnik, N.A., Simulation of Rock Strength and Sealing Performance of a Barrier Dam around Tailings, Sovr. Innovats. Tekhnol. Podgot. Inzh. Kadrov Gorn. Prom. Transport., 2016, no. 3, pp. 304–308.Google Scholar
  13. 13.
    Zaki, M.J. and Vagner, M. Jr., Data Mining and Analysis, Fundamental Concepts and Algorithm, New York: Cambridge University Press, 2014.Google Scholar
  14. 14.
    Naticchia, B., Vaccarini, M., and Carbonari, A., A Monitoring System for Real-Time Interference Control on Large Construction Sites, Automation in Construction, 2013, vol. 29, pp. 148–160.CrossRefGoogle Scholar

Copyright information

© Pleiades Publishing, Ltd. 2018

Authors and Affiliations

  • N. N. Mel’nikov
    • 1
  • A. I. Kalashnik
    • 1
    Email author
  • N. A. Kalashnik
    • 1
  • D. V. Zaporozhets
    • 1
  1. 1.Mining Institute Kola Science CenterRussian Academy of SciencesApatityRussia

Personalised recommendations