Skip to main content
SpringerLink
Log in

Research Status and Development Trends of Mine Floor Water Inrush Grade Prediction

  • State-of-the-Art Review
  • Published:
Geotechnical and Geological Engineering Aims and scope Submit manuscript

Abstract

According to the characteristics of mine floor water inrush, its influence factors can be summarized as the geological structure and mining pressure, the aquifer water properties, and the water resistance ability of floor strata; the mechanism of each influence factor is described herein. The research history and status of mine floor water inrush are introduced, and the commonly used prediction methods of mine floor water inrush grade are summarized and categorized as empirical formula methods and GIS technology, mathematical analysis methods, nonlinear mathematical analysis methods and simulation experiment methods; a detailed analysis of each method is presented. With the development of big data, cloud computing and nonlinear algorithm research, the existing deficiencies of floor water inrush prediction methods will likely be addressed by the future research and development trends of mine floor water inrush grade prediction.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Cao Q-K, Zhao F (2011) Forecast of water inrush quantity from coal floor based on genetic algorithm-support vector regression. J China Coal Soc 36(12):2097–2101

    Google Scholar 

  • Chen H-J, Li X-B, Liu A-H et al (2009) Forecast method of water inrush quantity from coal floor based on distance discriminant analysis theory. J China Coal Soc 34(4):487–491

    Google Scholar 

  • Chen K, Dong Q-H, Du Z-J et al (2013) Prediction model for coal mine floor water inrush and application based on fisher discrimination method. Saf Coal Mines 44(2):32–35

    Google Scholar 

  • Chen X, Li F et al (2015) Water inrush prediction of coal floor based on adaptive robust evidence theory. Ind Mine Autom 41(8):46–51

    Google Scholar 

  • Cheng X-Q, Jin X-L, Wang Y-Z et al (2014) Survey on big data system and analytic technology. J Softw 25(9):1889–1908

    Google Scholar 

  • Dong G, Huang H (2016) Using fuzzy comprehensive evaluation method to evaluate the risk of water inrush from coal seam floor. Coal Sci Technol Mag 1:107–110

    Google Scholar 

  • Feng Q-Y et al (2006) Numerical simulation on water-inrush from the seam floor based on the coupled analysis of seepage and damage. J Saf Environ 3:1–4

    Google Scholar 

  • Gao W, Wang Z (2013) Forecast of inrushed water volume grade from based on support vector machine with particle swarm optimization. Coal Geol Explor 40(6):44–47

    Google Scholar 

  • Guan E (2012) Origin of water bursting coefficient and process of modification. Coal Geol China 24(2):30–32

    Google Scholar 

  • Jiang A-N, Liang B (2005) Forecast of water inrush from coal floor based on least square support vector machine. J China Coal Soc 30(5):613–617

    Google Scholar 

  • Li B-Y (1999) “Down three zones” in the prediction of the water inrush from coalbed floor aquifer-theory, development and application. J Shandong Inst Min Technol Nat Sci 18(4):11–18

    Google Scholar 

  • Li Y (2007) Prediction method study on water inrush through coal floor based on support vector machines. Xi’an branch of China Coal Research Institute, Xi’an

    Google Scholar 

  • Li K, Wang C (1992) The technique measuring the stress of rock mass used in the study of the mechanism of the water-inrush from coal floor. Coal Geol Explor 3:32–33

    Google Scholar 

  • Li B et al (2014) Risk assessment of coal floor groundwater bursting based on fuzzy comprehensive evaluation-comprehensive weight. J Henan Polytech Univ Nat Sci 01:6–11

    Google Scholar 

  • Li B et al (2017) Influencing factors and prediction of mine water inrush disaster under thick unconsolidated layer and thin bedrock. J Shandong Univ Sci Technol Nat Sci 06:39–46

    Google Scholar 

  • Liao W, Zhou R-Y, Li S-Q (2006) Study on the non-linear forecast methods for water inrush from coal floor based on wavelet neural network. China Saf Sci J 16(11):24–28

    Google Scholar 

  • Liu H, Wang Z (1992) Coal mining on confined water. Coal Industry Press, Beijing

    Google Scholar 

  • Liu W, Zhang G (2002) Expert evaluation of water inrush from floor-hierarchy analysis prediction and evaluation. Geotech Investig Surv 1:22–25

    Google Scholar 

  • Liu W-T, Zhang W-Q, Li J-X (2000) An evaluation of the safety of floor water-irruption using analytic hierarchy process and fuzzy sythesis methods. J China Coal Soc 25(3):278–282

    Google Scholar 

  • Liu S, Chen L, Wang J et al (2013) Regional prediction of seam floor water inrush based on fuzzy cluster analysis and fuzzy pattern pecognition. Min Saf Environ Prot 40(2):85–88

    Google Scholar 

  • Liu W, Liu Y, Shen J (2014) Safety evaluation of floor water inrush in deep mining based on the fuzzy matter-element theory. J Shandong Univ Sci Technol Nat Sci 3:4

    Google Scholar 

  • Manyika J, Chui M, Brown B et al (2011) Big data: the next frontier for innovation, competition, and productivity. Analytics

  • Pan H, Wang J (2009) Forecast for water-inrush from coal floor based on neural networks trained by particle swarm optimization. Shanxi Cok Coal Sci Technol 1:34–36

    Google Scholar 

  • Pawlak Z (1982) Rough sets. Int J Comput Inform Sci 11(5):341–356

    Article  Google Scholar 

  • Qian M, Miao X, Xu J (1996) Theoretical study of key stratum in ground control. J China Coal Soc 21(31):44–47

    Google Scholar 

  • Qiao Y-W (2011) Application research of genetic algorithm and artificial neural networks in the prediction of mine water gushing-out. Xi’an University of Architecture and Technology, Xi’an

    Google Scholar 

  • Shi L, Yu X, Yin H et al (2008a) The theory of “four zones” and its application in the evaluation of water inrush from floor. China Coal Mine Geological Institute of Specialized Committee 2008 Academic Forum

  • Shi X-W, Huu Y-Q, Zhang H-S (2008b) GIS-based forecasting model of floor water bursting in coal mines. J Taiyuan Univ Technol S2:244–246

    Google Scholar 

  • State Administration of Work Safety and State Administration of Coal Mine Safety (2009) Provisions for mine water prevention

  • Sun P (2013) Application of rough set theory in prediction of floor water inrush. Inn Mong Coal Econ 10:112–113

    Google Scholar 

  • Sun W, Zhang S (2015) Development of floor water invasion of mining influence simulation testing system and its application. Chin J Rock Mechan Eng S1:3274–3280

    Google Scholar 

  • Sun M, Zheng W, Zhang W et al (2011) Discrimination system of combined grey matter-element for water-bursting in seam floor of deep mine. Coal Geol Explor 39(6):36–40

    Google Scholar 

  • Sun M et al (2013) Infiuence factors analysis for floor water bursting in deep coal seam mining based on analytic hierachy process. Saf Coal Mines 03:183–186

    Google Scholar 

  • Wang Z, Zhang J, Liu H (1995) Confined water close seams repeated mining floor rock moving the law. Coal Sci Technol 2:18–20

    Google Scholar 

  • Wang K, Wei A-Z, Chen Y-F et al (2004) Predicting method and its application of water inrush from coal floor based on catastrophe theory. China Saf Sci J 14(1):11–14

    Google Scholar 

  • Wei Z-J, Guo W-J, Zhu X-J et al (2012) Experimental study on mechanical simulation of mining pressure and overlying strata movement. Saf Coal Mines 43(9):50–52

    Google Scholar 

  • Wen G (2009) Research and development of forecast system for water inrush from mine coal bed floor based on GIS. Henan Polytechnic University, Jiaozuo

    Google Scholar 

  • Wu Q, Zhang Z, Zhang S et al (2007) A new practical methodology of the coal floor water bursting evaluating II: the vulnerable index method. J China Coal Soc 32(11):1121–1126

    Google Scholar 

  • Wu Q, Liu S, Jia G (2010) Application of vulnerable index method in the assessment of water outbursts from coal seam floor. China Coal 36(6):15–22

    Google Scholar 

  • Wu Q, Cui F-P, Zhao S-Q et al (2013) Type classification and main characteristics of mine water disasters. J China Coal Soc 38(04):561–565

    Google Scholar 

  • Xiao J-Y (2012) Study on evidence theory and its application to the water inrush prediction in mine. China University of Mining and Technology, Xuzhou

    Google Scholar 

  • Xiao J-Y, Tong M-M, Jiang C-L (2012) Prediction of water inrush quantity from coal floor based on fuzzy evidence theory. J China Coal Soc S1:131–137

    Google Scholar 

  • Xu X (1991) Prediction of water inrush from coal mine. Geological Publishing House, Beijing

    Google Scholar 

  • Xu Z et al (2012) Monitoring and numerical simulation of formation of water inrush pathway caused by coal mining above confined water with high pressure. Chin J Rock Mechan Eng 08:1698–1704

    Google Scholar 

  • Xu D, Cao S, Xu F (2014) Water inrush risk evaluation of coal seam floor based on catastrophe theory. Saf Coal Mines 45(12):197–200

    Google Scholar 

  • Xu S, Li B, Xu C-C (2015) Risk evaluation of coal floor water bursting based on fuzzy comprehensive evalution. Shangdong Coal Sci Technol 6:161–162

    Google Scholar 

  • Xue R et al (2010) Prediction of water inrush from floor based on particle swarm neural network. Energy Technol Manag 4:6–8

    Google Scholar 

  • Yang Z-L, Meng X-R et al (2013) Nonlinear prediction and evaluation of coal mine floor water inrush based on GA-BP neural network model. Saf Coal Mines 44(2):36–39

    Google Scholar 

  • Yin L (2011) Basic experimental study on water-inrush mechanism of floor in deep mining. Shandong University of Science and Technology, Qingdao

    Google Scholar 

  • Zhang W (2004) Study on the mechanism of water-bursting disaster from the floor of mine and it’s integrated judgement and measure and measure and the software exploitation of forecast system. Shandong University of Science and Technology, Qingdao

    Google Scholar 

  • Zhang G (2013) Study of the water-inrush risk evaluation based on both-branch fuzzy. Shandong University of Science and Technology, Qingdao

    Google Scholar 

  • Zhang J, Liu T (1990) On depth of fissured zone in seam floor resulted from coal extraction and its distribution characteristics. J China Coal Soc 2:35–38

    Google Scholar 

  • Zhang J, Zhang Y, Liu T (1997) Seepage of rock mass and water inrush from coal seam floor. Geological Publishing House, Beijing

    Google Scholar 

  • Zhang W-Q et al (2013) A model of Fisher’s discriminant analysis for evaluating water inrush risk from coal seam floor. J China Coal Soc 10:1831–1836

    Google Scholar 

  • Zhang W et al (2017) Research status and development trend of mine roof water inrush prediction. J Shandong Univ Sci Technol Nat Sci 06:15–23

    Google Scholar 

  • Zhong G-S, Jiang W-W, Xu G-Y (2007) Prediction of water inrush from floor based on catastrophe theory. J Liaoning Tech Univ Nat Sci 26(2):216–218

    Google Scholar 

  • Zhu Z (2014) Floor water inrush prediction based on risk evaluation and catastrophe theory. China University of Mining and Technology, Beijing

    Google Scholar 

Download references

Acknowledgements

This study was supported by the National Natural Science Foundation of China (No. 41472281).

Author information

Authors and Affiliations

  1. State Key Laboratory of Mining Disaster Prevention and Control Co-founded by Shandong Province and the Ministry of Science and Technology, Shandong University of Science and Technology, Qingdao, 266590, China

    Bo Li, Wenquan Zhang, Bing Gao & Jiudang Yuan

  2. College of Mining and Safety Engineering, Shandong University of Science and Technology, Qingdao, 266590, China

    Bo Li, Wenquan Zhang, Bing Gao & Jiudang Yuan

Authors
  1. Bo Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wenquan Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bing Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jiudang Yuan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bo Li.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, B., Zhang, W., Gao, B. et al. Research Status and Development Trends of Mine Floor Water Inrush Grade Prediction. Geotech Geol Eng 36, 1419–1429 (2018). https://doi.org/10.1007/s10706-017-0408-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10706-017-0408-4

Keywords

Search

Navigation