Skip to main content
Log in

Recognizing of Microseismic Source Types Based on Small-Aperture Seismic Array Data

  • Published:
Izvestiya, Physics of the Solid Earth Aims and scope Submit manuscript

Abstract—In this paper, we consider the problem of recording and processing the microseismic data with their subsequent interpretation and making the decisions concerning the probable threats associated with the violation of integrity of terrestrial environment due to mining activity. These decisions are made based on the detection of microseismic sources and recognition of their types by processing the multichannel seismograms from small-aperture seismic arrays. The procedures of seismogram processing include the algorithms for detecting the signals of microseismic sources in the noisy seismograms from the array sensors and the procedures for estimating various parameters of these sources. In this paper, we propose a new detection algorithm which is based on evaluating multiple coherence of the array seismograms and is capable of identifying the waves radiated from microseismic sources with complex focal mechanisms against the diffuse seismic noise. In contrast to the widely used STA/LTA array detector which is aimed at separating plane seismic waves, the proposed detector is intended for the recognition of waves from local seismic events in the complexly structured subsurface environment. Based on the numerical experiments with model and real seismic array data containing signals from the sources with complex focal mechanisms, it is shown that the types of microseismic sources can be recognized with the use of various algorithms of seismic array data analysis: with new algorithms for estimating the coordinates of microseismic sources and with traditional algorithms of space-time spectral analysis.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.
Fig. 8.
Fig. 9.
Fig. 10.
Fig. 11.
Fig. 12.
Fig. 13.

Similar content being viewed by others

REFERENCES

  1. Aki, K. and Richards, P., Quantitative Seismology: Theory and Methods, vols. 1, 2, San Francisco: Freeman, 1981.

  2. Anikiev, D., Valenta, J., Staněk, F., and Eisner, L., Joint location and source mechanism inversion of microseismic events: benchmarking on seismicity induced by hydraulic fracturing, Geophysical J. International, 2014, vol. 198, no. 1, pp. 249–258.

    Article  Google Scholar 

  3. Bendat, S. and Piersol, G., Random Data: Analysis and Measurement Procedures, 4th Edition, New York: Wiley Press, 2010.

    Book  Google Scholar 

  4. Bording, P., SeismicWave Propagation—Modeling and Inversion. Society of Exploration Geophysics, Oklahoma: Tulsa, 1996.

  5. Capon, J., High-resolution frequency-wavenumber spectrum analysis, Proceedings of the IEEE57, 1969, pp. 1408–1418.

    Article  Google Scholar 

  6. Cros, E., Roux, P., Vandemeulebrouck, J., and Kedar, S., Locating hydrothermal acoustic sources at old faithful geyser using matched field processing, Geophys. J. Int., 2017, vol. 187, no. 1. pp. 385–393.

    Article  Google Scholar 

  7. Droznin, D., Shapiro, N., Droznina, S., Senyukov, S., Chebrov, V., and Gordeev, E., Detecting and locating volcanic tremors on the Klyuchevskoy group of volcanoes (Kamchatka) based on correlations of continuous seismic records, Geophys. J. Int., 2015, vol. 203, pp. 1001–1010.

    Article  Google Scholar 

  8. Duncan, P.M., Lakings, J.D., and Flores, R.A., Method for passive seismic emission tomography, US Patent no. 7663970, 2010.

  9. Eisner, L., Williams-Stroud, S., Hill, A., Duncan, P., and Thornton, M., Beyond the dots in the box: Microseismicity-constrained fracture models for reservoir simulation, The Leading Edge, 2010, vol. 29, pp. 326–333.

    Article  Google Scholar 

  10. Hannan, E.J., Multiple Time Series Analysis, New York: John Willey and Sons, 1970.

    Book  Google Scholar 

  11. Herrmann, R.B., Computer programs in seismology: an evolving tool for instruction and research, Seismol. Res. Lett., 2013, vol. 84, pp. 1081–1088.

    Article  Google Scholar 

  12. Jollife, I., Principal Component Analyses, Berlin: Springer, 1986.

    Book  Google Scholar 

  13. Kiselevitch, V.L., Nikolaev, A.V., Troitskiy, P.A., and Shubik, B.M., Emission tomography: main ideas, results, and prospects, Proceedings of the 61st Annual International Meeting, SEG, Expanded Abstracts, 1991, p. 1602.

  14. Krim, H. and Viberg, M., Sensor Array Signal Processing: Two Decades Later, Boca Raton: CRC Press, 1995.

    Google Scholar 

  15. Kushnir, A., Varypaev, A., Dricker, I., Rozhkov, M., and Rozhkov, N., Passive surface microseismic monitoring as a statistical problem: location of weak microseismic signals in the presence of strongly correlated noise, Geophysical Prospecting, 2014, vol. 62, no. 4, pp. 819–833.

    Article  Google Scholar 

  16. Kushnir, A.F., Statisticheskiye i vychislitel’nyye metody seysmicheskogo monitoringa (Statistical and Computational Methods of Seismic Monitoring), Moscow: KRASAND, 2012.

  17. Kushnir, A.F. and Varypaev, A.V., Robustness of statistical algorithms for location of microseismic sources based on surface array data, Comp. Geoscience, 2017. https://doi.org/10.1007/s10596-017-9623-6

    Google Scholar 

  18. Kushnir, A.F., Varypaev, A.V., Rozhkov, M.V., Epiphansky, A.G., and Dricker, I., Determining the microseismic event source parameters from the surface seismic array data with strong correlated noise and complex focal mechanisms of the source, Izv.,Phys. Solid Earth, 2014, vol. 50, no. 3, pp. 334–354.

    Article  Google Scholar 

  19. Lyubushin, A., Global seismic noise synchronization and seismic danger, Second European Conference on Earthquake Engineering and Seismology, Istanbul, 2014, pp. 25–29.

  20. Malovichko, D.A. and Lynch, R.A., Micro-seismic monitoring of open-pit slopes, Mining Echo, 2006, vol. 24, no. 2, pp. 21–30.

    Google Scholar 

  21. Maochen, G., Efficient mine microseismic monitoring, Internat. J. Coal Geol., 2005, vol. 64, pp. 44–56.

    Article  Google Scholar 

  22. Marple, S., Digital Spectral Analysis. Englewood Cliffs, New York: Prentice-Hall, 1985.

    Google Scholar 

  23. Samson, J.C. and Olson, J.V., Data—adaptive polarization filter for multichannel geophysical data, Geophysics, 1982, vol. 46, no. 10, pp. 1423–1431.

    Article  Google Scholar 

  24. Singh, H. and Jha, R.M., Trends in adaptive array processing, Int. J. Antennas Propagation, 2012, vol. 2012, article ID 361768. https://doi.org/10.1155/2012/361768

    Article  Google Scholar 

  25. Stanek, F., Valenta, J., Anikiev, D., and Eisner, L., Semblance for microseismic event detection, Geophys. J. Int., 2014, vol. 201, pp. 1362–1369. https://doi.org/10.1093/gji/ggv070

    Article  Google Scholar 

  26. Stoica, P. and Moses, R., Spectral Analysis of Signals, New York: Prentice-Hall, 2005.

    Google Scholar 

  27. Varypaev, A.V., Sanina, I.A., Chulkov, A.B., and Kushnir, A.F., Application of robust phase algorithms for seismic emission recognition in region of mine explosions, Seism. Instrum., 2018, vol. 54, no. 2, pp. 33–48.

    Google Scholar 

  28. Zhang, C., Florêncio, D., Ba, D.E., and Zhang, Z., Maximum likelihood sound source localization and beam forming for directional microphone arrays in distributed meetings, IEEE Trans. Multimedia, 2008, vol. 10, no. 3, pp. 538–548.

    Article  Google Scholar 

Download references

Funding

The modeling and theoretical part of the work were supported under the research project no. AAAA-A19-119011490129-0. The full-scale experiment and processing of the corresponding measurements were carried out with the support from the Russian Science Foundation (project no. 16-17-00095).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. V. Varypaev.

Additional information

Translated by M. Nazarenko

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sanina, I.A., Riznichenko, O.Y., Kushnir, A.F. et al. Recognizing of Microseismic Source Types Based on Small-Aperture Seismic Array Data. Izv., Phys. Solid Earth 56, 260–278 (2020). https://doi.org/10.1134/S1069351320010127

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S1069351320010127

Keywords:

Navigation