Mining subsidence prediction for multi-seam and non-rectangular goafs based on probability integral model: a case study from China

Abstract

Ground subsidence associated with underground mining has caused environmental and economic damage in coal mining areas. So it is important to predict mining subsidence prior to any coal extraction. In order to predict mining subsidence based on probability integral model, we present a triangle subsection method for mining subsidence calculation of non-rectangular goafs. In the probability integral model, multi-seam subsidence is determined by using cumulative subsidence coefficients for different coal seams that reflect the amount of mining in a given region and by adding up the subsidence for every single coal seam in the research area. In the triangle subsection method, non-rectangular goafs are divided into several triangular areas rather than approximately rectangular areas, which can avoid errors resulting from the latter approximation method. The proposed method is then used to compare with rectangular subsection method to predict the subsidence induced by multi-seam non-rectangular goafs within a coal mine in the Liu Fangzi area of China as a case study. From the comparison, results show that the proposed approach can effectively deal with subsidence prediction related to non-rectangular goafs.

This is a preview of subscription content, access via your institution.

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

References

  1. Abidin HZ, Djaja R, Darmawan D, Hadi S, Akbar A, Rajiyowiryono H (2001) Land subsidence of Jakarta (Indonesia) and its geodetic monitoring system. Nat Hazards 23:365–387

    Article  Google Scholar 

  2. Arosio D, Laura L, Monica P, Luigi Z (2013) Seismic characterization of an abandoned mine site. Acta Geophysica 61(3):611–623

    Article  Google Scholar 

  3. Diao X, Wu K, Dawei Z, Liang L (2016) Integrating the probability integral method for subsidence prediction and differential synthetic aperture radar interferometry for monitoring mining subsidence in Fengfeng, China. J Appl Remote Sens 10(1):016–028

    Article  Google Scholar 

  4. Fan HD, Cheng D, Deng KZ, Chen BQ, Zhu CG (2015) Subsidence monitoring using D-InSAR and probability integral prediction modelling in deep mining areas. Surv Rev 47:438–445

    Article  Google Scholar 

  5. Formulated by National Coal Bureau of P.R.C (2000) Regulation of mining and pillar leaving under building, water-body, railway and main underground engineer. Coal Industry Press, Beijing, pp 81–90 (in Chinese)

    Google Scholar 

  6. Ghabraie B, Ren G, Smith JV (2017a) Characterising the multi-seam subsidence due to varying mining configuration, insights from physical modeling. Int J Rock Mech Min Sci 93(2017):269–279

    Article  Google Scholar 

  7. Ghabraie B, Ren G, Barbato J, Smith JV (2017b) A predictive methodology for multi-seam mining induced subsidence. Int J Rock Mech Min Sci 93:280–294

    Article  Google Scholar 

  8. He G (1982) Application of influence function of weber distribution to the precalculation of ground surface movement: a study on the fundamental law of ground movement based on the clastic theory. J China Univ Min Technol 01:1–20

    Google Scholar 

  9. He W (1993) Data processing system SDY for surface movement in coal mining. Shanxi mining Institute Learned Journal 11(3):230–240 (in Chinese)

    Google Scholar 

  10. He GQ, Yang L, Ling GD (1991) Mining subsidence. China University of Mining and Technology Press, Xuzhou, pp 118–147

    Google Scholar 

  11. Julio Miranda P, Ortíz Rodríguez AJ, Palacio Aponte AG, López Doncel R, Barboza Gudiño R (2012) Damage assessment associated with land subsidence in the San Luis Potosi-Soledad de Graciano Sanchez metropolitan area, Mexico, elements for risk management. Nat Hazards 64:751–765

    Article  Google Scholar 

  12. Kim K-D, Lee S, Hyun-Joo O, Choi J-K, Won J-S (2006) Assessment of ground subsidence hazard near an abandoned underground coal mine using GIS. Environ Geol 50:1183–1191

    Article  Google Scholar 

  13. Kratzsch H (1983) Mining subsidence engineering. Springer-Verlag, Berlin Heidelberg, New York

    Book  Google Scholar 

  14. Li R, Liu Ss, Fang L (2002) Ground subsidence predictions for highway underlaying multiplayer goaf. Journal of Southeast University (Natural Science Edition) 32(4):648–653

    Google Scholar 

  15. Li P-x, Tan Z-x, Deng K-z (2011) Calculation of maximum ground movement and deformation caused by mining. Trans Nonferrous Metals Soc China 21:562–569

    Article  Google Scholar 

  16. Liu BC, Liao GH (1965) The basic rule of surface movement of coal mine. China Industry Press, Beijing, pp 99–104

    Google Scholar 

  17. Longoni L, Monica P, Davide B, Diego A, Luigi Z (2016) The risk of collapse in abandoned mine sites: the issue of data uncertainty. Open Geosciences 8:246–258

    Article  Google Scholar 

  18. Lu B, Liu C, Liu D (2016) Research on the roof strata moving law in shallow thin bedrock with 3D physical simulation experiment. Journal of Sichuan University (Engineering Science Edition) 48:107–114

    Google Scholar 

  19. Ma W, Hu H (2013) The strata movement regularity and parameter simulation analysis in multiple seams repeated mining. Appl Mech Mater 295–298:2935–2939

  20. Ma J, Dong L, Zhao G, Li X (2019a) Qualitative method and case study for ground vibration of tunnels induced by fault-slip in underground mine. Rock Mech Rock Eng 52:1887–1901

    Article  Google Scholar 

  21. Ma J, Dong L, Guoyan Z, Xibing L (2019b) Ground motions induced by mining seismic events with different focal mechanisms. Int J Rock Mech Min Sci 116:99–110

    Article  Google Scholar 

  22. Maya I, Rudzinski L, Pawluszek-Filipiak K et al (2020) Combined study of a significant mine collapse based on seismological and geodetic data-29 January 2019, Rudna Mine, Poland. Remote Sens 12:1570

    Article  Google Scholar 

  23. Nie L, Zhang M, Jian H (2013) Analysis of surface subsidence mechanism and regularity under the influence of seism and fault. Nat Hazards 66:773–780

    Article  Google Scholar 

  24. Peng SS (1992) Surface subsidence engineering. Colorado: Society for Mining, Metallurgy and Exploration:13–15

  25. Peng S, Qin S, Li G (2019) Predicting expressway subsidence based on niching genetic algorithm and holt–winters model. Arab J Geosci 12:354

    Article  Google Scholar 

  26. Ryszard H, Witkowski WT, Guzy A, Malinowska A (2020) Identification of the ground movements caused by mining-induced seismicity with the satellite interferometry. Proc IAHS 382:297–301

    Article  Google Scholar 

  27. Son M, Moon H-K, Kim Y, Lee S-A (2017) A study on the subsidence risk evaluation using 3-D rock mass collapse simulation for abandoned mines. Geosystem Engineering 20(1):51–58

    Article  Google Scholar 

  28. Sui W, Yuan H, Ma L (2015) Interactions of overburden failure zones due to multiple-seam mining using longwall caving. Bull Eng Geol Environ 74:1019–1035

    Article  Google Scholar 

  29. Tong L, Lian L, Binod A, Songyu L (2016) Risk assessment and remediation strategies for highway construction in abandoned coal mine region: lessons learned from Xuzhou, China. Bull Eng Geol Environ 75:1045

    Article  Google Scholar 

  30. Tugrul U, Akcin H, Yilmaz O (2013) An integrated approach for the prediction of subsidence for coal mining basins. Eng Geol 166:186–203

    Article  Google Scholar 

  31. Wang D-c, Yang Y-J, Wang K et al (2012) Numerical simulation of study on rupture development rules of overburden strata in repeated mining. Adv Mater Res 433-440:1933–1939

    Article  Google Scholar 

  32. Williams S, Bock Y, Pang P (1998) Integrated satellite interferometry: tropospheric noise, GPS estimates and implications for interferometric synthetic aperture radar products. Geophysics 103(11):051–067

    Google Scholar 

  33. Xue JQ (2012) Research of monitoring mine subsidence by D-InSAR technique. MSc thesis. China University of Mining and Technology

  34. Zhang Y (1993) Principle and program for calculation of rock strata and surface movement. China Coal Industry Publishing House, Beijnging, pp 104–109

    Google Scholar 

  35. Zhao J, Sun Z, Zhang Z, Liu T (2010) A brief analysis of the collapse mechanism and development factors of the multilayer goaf. Gr Water 32(2):158–161

    Google Scholar 

Download references

Acknowledgements

We thank the journal editor for useful comments and careful handling of the manuscript. We are grateful to the anonymous reviewer for constructive comments that improved the quality of this paper.

Funding

This research was funded by the Jilin Provincial Science and Technology Department (No. 20190303103SF), the National Science Foundation of China (Grant No. 41602230), and a China Geological Survey project (Grant No. DD20160026).

Author information

Affiliations

Authors

Corresponding author

Correspondence to Shuaiying Peng.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Additional information

Responsible editor: Murat Karakus

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Peng, S., Qin, S., Wang, M. et al. Mining subsidence prediction for multi-seam and non-rectangular goafs based on probability integral model: a case study from China. Arab J Geosci 14, 1231 (2021). https://doi.org/10.1007/s12517-021-07620-3

Download citation

Keywords

  • Ground subsidence
  • Probability integral model
  • Triangle subsection
  • Multi-seam goafs
  • Non-rectangular goafs