Skip to main content
Log in

Study on the law of initial gas expansion energy and its feasibility in coal and gas outburst prediction

  • Research Article
  • Published:
Environmental Science and Pollution Research Aims and scope Submit manuscript

Abstract

In order to explore the relationship between IEERG and outburst intensity and verify the feasibility of the former in predicting coal and gas outburst, a series tests with different gases and different gas pressures were conducted on the basis of self-developed coal and gas outburst simulation system and IEERG measuring instrument. The results show that with the increase of gas pressure, the IEERG increases gradually. Under the same gas pressure, the coal has the strongest adsorption capacity for CO2, followed by CH4 and N2. When the IEERG is less than 24.40 mJ·g−1, no outburst will occur. When the IEERG is greater than 24.40 mJ·g−1, weak outburst will occur. When the IEERG is greater than 34.72 mJ·g−1, strong outburst will occur. This shows that the magnitude of IEERG is closely related to the outburst. The larger the IEERG, the greater the possibility of outburst and the greater the intensity of outburst. It is feasible to predict the risk of outburst using IEERG, and it can be quantified.

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

Similar content being viewed by others

Data availability

The data used to support the findings of this study are available from the corresponding author upon request.

References

  • An F, Yuan Y, Chen X, Li Z, Li L (2019) Expansion energy of coal gas for the initiation of coal and gas outbursts. Fuel 235:551–557

    Article  CAS  Google Scholar 

  • Cai Y, Wu S, Zhou M, Gao S, Yu H (2021) Early warning of gas concentration in coal mines production based on probability density machine. Sensors 21:5730

  • Cao J, Hu Q, Gao Y, Li M, Sun D (2021) Gas expansion energy model and numerical simulation of outburst coal seam under multifield coupling. Geofluids 2021:5552108

  • Chen Y, Yang D, Tang J, Li X, Jiang C (2018) Determination method of initial gas desorption law of coal based on flow characteristics of convergent nozzle. J Loss Prev Process Ind 54:222–228

    Article  Google Scholar 

  • Chen J, Zhu C, Du J, Pu Y, Pan P, Bai J, Qi Q (2022) A quantitative pre-warning for coal burst hazardous zones in a deep coal mine based on the spatio-temporal forecast of microseismic events. Process Saf Environ Prot 159:1105–1112

    Article  CAS  Google Scholar 

  • Du J, Chen J, Pu Y, Jiang D, Chen L, Zhang Y (2021) Risk assessment of dynamic disasters in deep coal mines based on multi-source, multi-parameter indexes, and engineering application. Process Saf Environ Prot 155:575–586

    Article  CAS  Google Scholar 

  • Guo B, Li Y, Jiao F, Luo T, Ma Q (2018) Experimental study on coal and gas outburst and the variation characteristics of gas pressure. Geomech Geophys Geo-Energy Geo-Resour 4:355–368

    Article  Google Scholar 

  • He X, Zhou S (1994) Rheological hypothesis of coal and gas outburst mechanism. Int J Min Sci Technol 4:15–23

  • Hou W, Wang H, Yuan L, Wang W, Xue Y, Ma Z (2021) Experimental research into the effect of gas pressure, particle size and nozzle area on initial gas-release energy during gas desorption. Int J Min Sci Technol 31:253–263

    Article  Google Scholar 

  • Jiang C, Xu L, Li X, Tang J, Chen Y, Tian S, Liu H (2015) Identification model and indicator of outburst-prone coal seams. Rock Mech Rock Eng 48:409–415

    Article  Google Scholar 

  • Li J, Hu Q, Yu M, Li X, Hu J, Yang H (2019) Acoustic emission monitoring technology for coal and gas outburst. Energy Sci Eng 7:443–456

    Article  Google Scholar 

  • Li B, Wang EY, Shang Z, Liu XF, Li ZH, Li BL, Wang H, Niu Y, Song Y (2021b) Optimize the early warning time of coal and gas outburst by multi-source information fusion method during the tunneling process. Process Saf Environ Prot 149:839–849

    Article  CAS  Google Scholar 

  • Li B, Wang E, Shang Z, Li Z, Li B, Liu X, Wang H, Niu Y, Wu Q, Song Y (2021a) Deep learning approach to coal and gas outburst recognition employing modified AE and EMR signal from empirical mode decomposition and time-frequency analysis. J Nat Gas Sci Eng 90:103942

  • Liang Y, Wang F, Li X, Jiang C, Li L, Chen Y (2018) Study on the influence factors of the initial expansion energy of released gas. Process Saf Environ Prot 117:582–592

    Article  CAS  Google Scholar 

  • Liu Z, Wang H, Wang S, Zhang B, Wang S (2020) A high-precision and user-friendly triaxial apparatus for the measurement of permeability of gassy coal. Measurement 154:107496

    Article  Google Scholar 

  • Miao S, Pan P, Konicek P, Yu P, Liu K (2021) Rock damage and fracturing induced by high static stress and slightly dynamic disturbance with acoustic emission and digital image correlation techniques. J Rock Mech Geotech Eng 13:1002–1019

    Article  Google Scholar 

  • Pu Y, Chen J, Apel DB (2021) Deep and confident prediction for a laboratory earthquake. Neural Comput Appl 33(18):11691–11701

    Article  Google Scholar 

  • Qiu L, Li Z, Wang E, Liu Z, Ou J, Li X, Ali M, Zhang Y, Xia S (2018) Characteristics and precursor information of electromagnetic signals of mining-induced coal and gas outburst. J Loss Prev Process Ind 54:206–215

    Article  Google Scholar 

  • Su G, Hu L, Feng X, Yan L, Zhang G, Yan S, Zhao B, Yan Z (2018) True triaxial experimental study of rockbursts induced by ramp and cyclic dynamic disturbances. Rock Mech Rock Eng 51:1027–1045

    Article  Google Scholar 

  • Wang H, Wang E, Li Z (2020) Study on dynamic prediction model of gas emission in tunneling working face. Combust Sci Technol 194:1–17

  • Wang C, Wei L, Hu H, Wang J, Jiang M (2022) Early warning method for coal and gas outburst prediction based on indexes of deep learning model and statistical model. Front Earth Scie 10:811978

  • Xu L, Jiang C (2017) Initial desorption characterization of methane and carbon dioxide in coal and its influence on coal and gas outburst risk. Fuel 203:700–706

    Article  CAS  Google Scholar 

  • Xu L, Jiang C, Tian S (2014) Experimental study of the gas concentration boundary condition for diffusion through the coal particle. J Nat Gas Sci Eng 21:451–455

    Article  Google Scholar 

  • Yang W, Lin BQ, Zhai C, Li XZ, An S (2012) How in situ stresses and the driving cycle footage affect the gas outburst risk of driving coal mine roadway. Tunn Undergr Space Technol 31:139–148

    Article  CAS  Google Scholar 

  • Yang D, Pan L, Chen Y, Tang J (2021) Comparison of outburst hazard of coal with different failure types: a case study. Energy Sour Part A Recov Util Environ Effects 2021:1–13

  • Yu K, Qiang W (2020) Application of ant colony clustering algorithm in coal mine gas accident analysis under the background of big data research. J Intell Fuzzy Syst 38:1381–1390

    Article  Google Scholar 

  • Zhang J, Ai Z, Guo L, Cui X (2021) Research of synergy warning system for gas outburst based on entropy-weight Bayesian. Int J Comput Intell Syst 14:376–385

    Article  Google Scholar 

  • Zhang C, Yang D, Tang J, Han Y, Chen Y, Yang S, Jiang C (2022) Study on normalization of critical values of the prediction indicator initial gas emission from boreholes. Environ Earth Sci 81:27

  • Zhao X, Sun H, Cao J, Ning X, Liu Y (2020) Applications of online integrated system for coal and gas outburst prediction: a case study of Xinjing Mine in Shanxi, China. Energy Sci Eng 8:1980–1996

    Article  Google Scholar 

Download references

Funding

The financial and general supports for this research were provided by the National Natural Science Foundation of China (52,227,901) and the Natural Science Foundation of Shandong Province (2019GSF111036).

Author information

Authors and Affiliations

Authors

Contributions

Zhongzhong Liu: methodology and writing.

Hanpeng Wang: conceptualization.

Bing Zhang: investigation.

Shitan Gu: supervision.

Corresponding author

Correspondence to Hanpeng Wang.

Ethics declarations

Ethics approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Conflict of interest

The authors declare no competing interests.

Additional information

Responsible Editor: Shimin Liu

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, Z., Wang, H., Zhang, B. et al. Study on the law of initial gas expansion energy and its feasibility in coal and gas outburst prediction. Environ Sci Pollut Res 30, 60121–60128 (2023). https://doi.org/10.1007/s11356-023-26792-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11356-023-26792-x

Keywords

Navigation