Seismic information processing algorithms

The seismic information processing methods in mine geomonitoring systems are reviewed. Geomonitoring is effectively used in coal mines in USA, Canada, South Africa, Great Britain, Australia and many other countries. Implementation and operation of geomonitoring systems in mines in Kuzbass, Vorkuta, Norilsk and Tashtagol used equipment of Russian and foreign manufacture (GITS, RELLS, ISS, ASKM, Prognoz-ADS etc.). Processing and effective interpretation of seismic data can use: cluster analysis, neural networks, system-analysis and synthesis toward synergistic effect, multilevel hierarchy, complexing of seismic monitoring with deformation, geodetic and electrophysical observations and crossborehole tomography, spectral analysis of seismograms, tuning-out of background effects at weak signals and pendulum wave studies. The main characteristics of the geodynamic behavior of rock mass are the coordinates of a seismic signal source, the intensity of seismic activity and the energy of seismic event. The developed algorithms of the seismic event source location are based on the cyclic selection of the coordinates of a reference point by minimizing the value of difference between the actual and theoretical delays of seismic wave arrivals and by minimizing the objective function by the adaptive random search using the random number generator (Monte-Carlo method). The integrated characteristic of seismic activity in rock mass is proposed to be the index F which integrates the ratio of current and background energies of a seismic event and the total seismic activity in the estimated period of time. The factor analysis determines the F index as function of: the linear size of 3D analysis matrix representing real-life rock mass; the increment in this linear size; the time interval.

Razumov E. E., Prostov S. M., Mulev S. N., Rukavishnikov G. D. Seismic information processing algorithms. MIAB. Mining Inf. Anal. Bull. 2022;(2):17-29. [In Russ]. DOI: 10.25018/0236_1493_2022_2_0_17.

E.E. Razumov^1,2, Assistant, Researcher, e-mail: razumov@vnimi.ru, ORCID ID: 0000-0002-3696-8553,
S.M. Prostov¹, Dr. Sci. (Eng.), Professor, e-mail: psm.kem@mail.ru, ORCID ID: 0000-0003-0780-2690,
S.N. Mulev², Director of Science, e-mail: smuleva@yandex.ru,
G.D. Rukavishnikov², Head of Geodynamic Monitoring Center, e-mail: geodmiruk@gmail.com, ORCID ID: 0000-0001-8228-2870,
¹ T. Gorbachev Kuzbass State Technical University, 650000, Kemerovo, Russia,
² Research Institute of Mining Geomechanics & Mine Surveying (VNIMI), 199106, Saint-Petersburg, Russia.

E.E. Razumov, e-mail: razumov@vnimi.ru.

1. Egorov A. P., Ryzhov V. A. On the issue of systematization of geophysical studies of the geomechanical state of the rock mass and the earth's surface for operational control of safe mining operations at coal mines. Ugol’. 2019, no. 10, pp. 29—33. [In Russ].

2. Razumov E. E., Rukavishnikov G. D., Mulev S. N., Prostov S. M. Basic principles of building a geomonitoring seismic system. Gornyi Zhurnal. 2021, no. 1, pp. 8—12. [In Russ].

3. Abdrakhmanov M. I., Lapin S. E., Shnayder I. V. Clustering algorithms in express-analysis of seismic data. MIAB. Mining Inf. Anal. Bull. 2019, no. 6, pp. 27—44. [In Russ]. DOI: 10.25018/0236-1493-2019-06-0-27-44.

4. Zhuravlev E. I., Zhuravlev E. I., Pikel' K.S. Automated forecast the stress state of the rock mass on the basis of extrapolation characteristics of seismic and seismic acoustic emission using a neural network technologies. MIAB. Mining Inf. Anal. Bull. 2015, no. 9, pp. 404—410. [In Russ].

5. Zhang M., Liu S., Chen S., Chen Y., Xu G., Qian D. Focus energy determination of mining microseisms using residual seismic wave attenuation in deep coal mining. Hindawi Shock and Vibration. 2018, vol. 2018, pp. 13.

6. Zhebel O., Eisner L. Simultaneous microseismic event localization and source mechanism determination. Geophysics. 2015, vol. 80, no. 1, pp. KS1–KS9.

7. Marcak H., Mutke G. Seismic activation of tectonic stresses by mining. Journal of Seismology. 2013, vol. 17, no. 4, pp. 1139—1148.

8. Chambers D. J. A., Boltz M. S., Richardson J. R., Finley S. A. Application of subspace detection on a surface seismic network monitoring in deep silver mine. Deep Mining 2017: Proceedings of the Eighth International Conference on Deep and High Stress Mining, Australian Centre for Geomechanics, Perth, pp. 141—154.

9. Rasskazov I. Yu., Gladyr A. V., Katella E. A., Miroshnikov V. I. Development of the complex geodynamic multilevel system for burst-hazard rock mass monitoring. MIAB. Mining Inf. Anal. Bull. 2014, no. 9, pp. 113—120. [In Russ].

10. Bodin V. V. Influence of local and intensezonesof tectonic faults on spatil distribution of spectrum of seismic waves. MIAB. Mining Inf. Anal. Bull. 2014, no. 4, pp. 5—10. [In Russ].

11. GITS — Sistema seysmicheskogo monitoringa. Ugol'. 2019, no. 10, pp. 34. [In Russ].

12. Sadovskiy M. A. Blochno-ierarkhicheskaya model' gornoy porody i ee ispol'zovanie v zadachakh seysmologii. Eksperimental'nye i chislennye metody v fizike ochaga zemletryaseniy [Experimental and numerical methods in earthquake focus physics], Moscow, Nauka, 1989, pp. 5—13.

13. Storcheus A. V. Calculating the seismic energy of earthquakes and explosions. Journal of Volcanology and Seismology. 2011, no. 5, pp. 49—59.

14. Jones M. T. Programmirovanie iskusstvennogo intellekta v prilozheniyakh [All Application Programming Программирование искусственного интеллекта в приложениях], Moscow, DMK Press, 2004, 312 p.

15. Elkin D. I. Tyakhti A. S. Metod otzhiga [Annealing method], Moscow, Mir, 2008, 48 p.