Advertisement

Experimental seismic attributes of gas-bearing anthracite

  • Bo Wang
  • Shengdong LiuEmail author
  • Fubao Zhou
  • Jialin Hao
GMGDA 2019
  • 38 Downloads
Part of the following topical collections:
  1. Geological Modeling and Geospatial Data Analysis

Abstract

Coal mine accidents have seriously constrained the development of energy economy, in which coal and gas outburst accidents pose the greatest impact, accounting for more than 70% of the accident rate. At present, the mine usually uses the parameters to evaluate the risk of outburst, such as gas desorption index and drilling yield index. However, the traditional index method has the shortcomings of time lag, complicated operation, and difficult real-time monitoring. In this paper, the advanced detection method of multi-component seismic wave is used to obtain the seismic attributes in real time and fast way, and three-component reception and artificial hammer excitation are arranged in the roadway. The field tests were carried out on nine roadways of No. 3 anthracite in Yangquan Mining Area, China. The correlation between the absolute gas emission quantity and attributes of the seismic wave was studied. The results show that under the same coal seam, the correlation between the absolute gas emission quantity and the seismic wave velocity parameters is weak. The absolute gas emission quantity has a good exponential correlation with the quality factor Q, the attenuation coefficient α, and the dominant frequency value fm. The absolute gas emission quantity is negatively correlated with the quality factor Q, and the regression equation is Qg = 3.5644e−0.33Q with correlation coefficient R2 = 0.9126. With the increase of absolute gas emission quantity, the attenuation coefficient of gas-bearing anthracite rises, but the dominant frequency decreases. On account of the high correlation between the absolute gas emission quantity and the quality factor, real-time monitoring of the quality factor of seismic wave have theoretical significance for predicting coal and gas outburst, and it is expected to provide a new way of the prediction of the outburst risk.

Keywords

Coal and gas outburst Seismic wave Absolute gas emission quantity Quality factor 

Notes

Acknowledgments

This research has been performed by the Fundamental Research Funds for the Central Universities (2017QNB11).

References

  1. Gao JL, Wang Y (2011) Research on the relationship between the drilling cutting gas desorption index and parameters of gas occurrence. J Appl Mech Mater 99-100:1312–1318CrossRefGoogle Scholar
  2. Hao F, Liu M, Zuo W (2014) Coal and gas outburst prevention technology and management system for Chinese coal mines: a review, Proceedings of the 22nd MPES Conference, 581-600.CrossRefGoogle Scholar
  3. He XQ, Nie BS, Liu XF, Wang EY (2007) Application of electromagnetic radiation technology in monitoring and warning on coal and rock dynamic disasters. J Liaoning Tech Univ 32(1):56–59Google Scholar
  4. Hu CY, Peng SP, Du WF, Gao JW (2011) Seismic AVO inversion and coal-gas outburst area prediction. Nat Gas Geosci 22(4):728–732Google Scholar
  5. Li JJ, Li FJ, Hu MS, Zhang W, Pan DM (2017) Evaluation of geological conditions for coalbed methane occurrence based on 3D seismic information: a case study in Fowa region, Xinjing coal mine, China. Acta Geophys 65(2):345–351CrossRefGoogle Scholar
  6. Lu SL, He JS, Li ZB (2000) Non-contact prediction methods for coal and gas outbursts. Geophys Geochem Explor 24(1):23–27Google Scholar
  7. Lu J, Wang Y, Sri Y (2011) Coal hardness prediction using joint inversion of multi-wave seismic data and logging. Chinese J Geophys 54(11):2967–2972Google Scholar
  8. Peng SP, Gao YF, Yang RZ (2005) Theory and application of AVO for detection of coalbed methane-a case from the Huainan coalfield. Chinese J Geophys, 48(6): 1475-1486.Google Scholar
  9. Peng SP, Du WF, Yuan CF, Gou JG, He BS (2008) Identification and forecasting of different structural coals by P-wave and S-wave from well-logging. Acta Geologica Sinica 82(10):1311–1322Google Scholar
  10. Peng SP, Du WF, Yan CY, Ju GG (2014) Coal-bed gas content prediction based on AVO inversion. J China Coal Soc 39(9):1792–1796Google Scholar
  11. Qi WS, Jin LZ, Yang ZJ (2008) Assessment and application of elastic wave features of mine coal and gas outburst. Coal Sci Technol 36(8):37–41Google Scholar
  12. Wang EY, He XQ, Nie BS, Liu ZT (2000) Principle of predicting coal and gas outburst using electromagnetic emission. J China Univ Min Technol 29(3):225–229Google Scholar
  13. Wang ZJ, Liu SD, Lu T, Zhang P, Zhao LG (2011) Experimental study on the relationships of coal gas and seismic attributes. Coal Geol Explor 39(5):63–65Google Scholar
  14. Wang EY, Li ZH, He XQ, Chen L (2014a) Application and pre-warning technology of coal and gas outburst by electromagnetic radiation. Coal Sci Technol 42(6):53–57Google Scholar
  15. Wang YG, Li MG, Li M, Dai SH (2014b) Analysis on influence factors of ultrasonic parameters for tectonic coal. J Saf Sci Technol 10(7):82–86Google Scholar
  16. Xiao HF, He XQ, Wang EY, Sa ZY (2003) Determination application of critical value in coal and gas outburst prediction by electromagnetic emission method. J China Coal Soc 28(5):465–469Google Scholar
  17. Yu G, Vozoff K, Durney DW (1991) Effects of confining pressure and water saturation on ultrasonic compressional wave velocities in coals. Int J Rock Mech Min 28(6):515–522CrossRefGoogle Scholar
  18. Zhao QF, Hou Y, Liu SX (2008) The pilot study on characteristics of the seismic wave spectrum and gas content of coal seam. J Henan Ploy Univ 27(6):615–618Google Scholar

Copyright information

© Saudi Society for Geosciences 2019

Authors and Affiliations

  • Bo Wang
    • 1
  • Shengdong Liu
    • 1
    Email author
  • Fubao Zhou
    • 2
  • Jialin Hao
    • 1
  1. 1.State Key Laboratory of Deep Geomechanics & Underground Engineering and School of Resource and Earth ScienceChina University of Mining and TechnologyXuzhouChina
  2. 2.School of Safety EngineeringChina University of Mining and TechnologyXuzhouChina

Personalised recommendations