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Risk Assessment of Water Inrush in an Underground Coal Mine Based on GIS and Fuzzy Set Theory

基于GIS与模糊集理论的矿井突水风险评价

Risikoabschätzung für einen Wassereinbruch in eine unterirdische Kohlemine auf Basis von GIS und der Fuzzy-Mengen-Theorie

Relevamiento del riesgo de irrupción de agua en una mina subterránea de carbón basado en GIS y en la teoría de conjuntos difusos

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Abstract

A systematic method was developed to evaluate the risk of water inrush through a coal seam floor using the geographic information system (GIS) and the fuzzy set theory. The main geological and hydrogeological indicators that control water inrush were first considered using a fuzzy mathematics approach, in which fractal analysis was carried out to quantify the fault’s characteristics. The degree of membership was determined using GIS, the weight of every factor was considered by calculating the entropy in accordance with Shannon’s information entropy theory, and the level of risk of the evaluated object was derived using the maximum membership principle. The approach was validated by a case study at the Chensilou mine in Henan Province, China, where the aquifers that underlie an exploitable coal seam, II2, were made impermeable by grouting. Data from Nov. 2014 to April 2016 shows that the risk of water inrush was reduced in Panel 2517 of the II2 coal seam, that there were no serious disturbances in this panel and no groundwater inrush through the floor. This method can be a powerful tool for systematically assessing the risk of water inrush through the floor, since the influence of several factors can be quantitatively considered in accordance with the geological and mining conditions.

摘要

基于地理信息系统(GIS)和模糊集理论提出了一种煤层底板突水危险评估方法。采用分形法量化断层特征,模糊集方法识别控制煤层底板突水的地质和水文地质主控因素。采用GIS方法确定隶属度,Shannon信息熵法确定主控因素权重,最大隶属度原则评价底板突水风险水平。通过河南省永城陈四楼煤矿2517工作面工程案例验证了评估方法可行性,该工作面煤层底板含水层经过注浆加固。2014年11月至2016年4月数据显示2517综采工作面突水危险性低;实际开采过程亦没有发生底板突水。该方法能够量化地质及采矿等影响,为一种系统评价煤层底板突水危险的工具。

Zusammenfassung

Eine systematische Methode auf Basis von geografischen Informationssystemen (GIS) und Fuzzylogic-Theorie wurde entwickelt um das Risiko eines Wassereinbruchs durch den Grund einer Kohlenmine zu untersuchen. Die wichtigsten geologischen und hydrogeologischen den Wassereinbruch kontrollierenden Indikatoren wurden zuerst mit einem Fuzzy-Ansatz, in dem fraktale Analyse durchgeführt wurde, u geprüft , um die Eigenschaften der Störungen zu quantifizieren. Der Grad der Beteiligung wurde mit GIS bestimmt, die Wichtung jedes Faktors wurde durch die Berechnung der Entropie nach Shannon's Informationstheorie und die Gefahrenstufe jedes untersuchten Objekts wurde nach dem Maximum-Member-Prinzip abgeleitet. Der Ansatz wurde an einer Studie in der Chensilou Mine in der Henan Provinz, China, wo der Aquifer im Liegenden einer kohlebürtigen Schicht durch Verpressung abgedichtet wurde, validiert. Daten zwischen November 2014 und April 2016 zeigen, dass das Risiko eines Wassereinbruchs in Plattform 2517 des Flözes II2 reduziert wurde und dass keine ernsthaften Beeinträchtigungen auf dieser Ebene und keine Grundwasserzutritte durch die Sohle auftraten. Diese Methode kann ein mächtiges Werkzeug sein, um das Risiko eines Wassereinbruchs durch die Sohle systematisch zu beurteilen, da der Einfluss mehrerer Faktoren entsprechend den geologischen Verhältnissen und den Abbaubedingungen quantitativ berücksichtigt werden kann.

Resumen

Un método sistemático fue desarrollado para evaluar el riesgo de irrupción de agua a través de una veta de carbón en el piso usando información geográfica y la teoría de conjuntos difusos. Los principales indicadores geológicos y hidrogeológicos que controlan la irrupción de agua fueron considerados inicialmente usando una aproximación de matemáticas difusa, en la cual el análisis fractal fue utilizado para cuantificar las características de la falla. El grado de pertenencia fue obtenido usando GIS, el peso de cada factor fue considerado calculando la entropía en acuerdo con la teoría de Shannon y el nivel de riesgo del objeto evaluando fue derivada usando el principio de máxima pertenencia. La aproximación fue validada para un caso de estudio en la mina Chensilou en la provincia de Henan, China, donde los acuíferos que rodean una veta explotable de carbón, II2, se hicieron impermeables por cementación. Los datos desde Nov. 2014 hasta Abril 2016 muestran que el riesgo de irrupción de agua fue reducido en el panel 2517 de la veta II2, que no hubieron serios disturbios en este panel y que no hubo irrupción de agua subterránea a través del piso. Este método puede ser una herramienta efectiva para el relevamiento sistemático del riesgo de irrupción de agua a través del piso, ya que la influencia de varios factores puede ser cuantitativamente considerada en acuerdo con las condiciones geológicas y de explotación minera.

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References

  • Berry MV, Lewis ZV (1980) On the Weierstrass-Mandelbrot fractal function. P R Soc Lond A-Cont 370(1743): 459–484

    Article  Google Scholar 

  • Chang PT, Huang LC, Lin HJ (2000) The fuzzy Delphi method via fuzzy statistics and membership function fitting and an application to the human resources. Fuzzy Set Syst 112(3): 511–520

    Article  Google Scholar 

  • Chen L, Feng X, Xie W, Xu D (2016) Prediction of water-inrush risk areas in process of mining under the unconsolidated and confined aquifer: a case study from the Qidong coal mine in China. Environ Earth Sci 75(8):1–17

    Google Scholar 

  • Chen LW, Qin Y, Gui HR, Zhang SL (2012) Analysis on probability of water inrush and quicksand in different mining sequences under an unconsolidated alluvium aquifer by fluid-solid coupling theory. J Coal Sci Eng 18(1):60–66

    Article  Google Scholar 

  • Chen JM, Yang RS (2011) Analysis of mine water inrush accident based on FTA. Proc Environ Sci 11:1550–1554

    Article  Google Scholar 

  • Christiansen AV, Auken E, Sørensen K (2009) The transient electromagnetic method. Groundwater geophysics, Springer, Berlin, pp 179–226

    Book  Google Scholar 

  • Coulson MR (1987) In the matter of class intervals for choropleth maps: with particular reference to the work of George F Jenks. Cartographica 24(2):16–39

    Article  Google Scholar 

  • Dombi J (1990) Membership function as an evaluation. Fuzzy Set Syst 35(1):1–21

    Article  Google Scholar 

  • Dong DL, Sun WJ, Xi S (2012) Water-inrush assessment using a GIS-based Bayesian network for the 12–2 coal seam of the Kailuan Donghuantuo coal mine in China. Mine Water Environ 31(2):138–146

    Article  Google Scholar 

  • Evans IS (1977) The selection of class intervals. T I Brit Geogr 2(1):98–124

    Article  Google Scholar 

  • Fryer P, Ruis J (2004) What are Fractal Systems? http://www.fractal.org/Fractal-systems.htm. Accessed 18 June 2004

  • Gu XG, Wang JC, Liu YD (2010) Water resistant features of high-risk outburst coal seams and standard discriminant model of mining under water-pressure. Min Sci Technol 20(6):797–802

    Google Scholar 

  • Guo BH (2008) Numerical analysis on water-inrush process due to floor heave. J Coal Sci Eng 14:225–229

    Article  Google Scholar 

  • Han J, Shi LQ, Yu XG, Wei JC, Li SC (2009) Mechanism of mine water-inrush through a fault from the floor. Min Sci Technol 19(3):276–281

    Google Scholar 

  • Hang Y, Zhang GL, Yang GY (2009) Numerical simulation of dewatering thick unconsolidated aquifers for safety of underground coal mining. Mining Sci Technol 19(3):312–316

    Google Scholar 

  • Huang HF, Mao XB, Yao BH, Pu H (2012) Numerical simulation on fault water-inrush based on fluid-solid coupling theory. J Coal Sci Eng 18(3):291–296

    Article  Google Scholar 

  • Jenks GF (1963) Generalization in statistical mapping. Ann Assoc Am Geogr 53(1):15–26

    Article  Google Scholar 

  • Jiang ZH (2011) Numerical analysis of the destruction of water-resisting strata in a coal seam floor in mining above aquifers. Min Sci Technol 21(4):537–541

    Google Scholar 

  • Kaufmann A, Gupta MM (1988) Fuzzy Mathematical Models in Engineering and Management Science. Elsevier Science, North Holland

    Google Scholar 

  • Klir G, Yuan B (1995) Fuzzy sets and fuzzy logic, vol 4. Prentice Hall, NJ

    Google Scholar 

  • Kong HL, Miao XX, Wang LZ, Zhang Y, Chen ZQ (2007) Analysis of the harmfulness of water-inrush from coal seam floor based on seepage instability theory. J China Univ Mining Technol 17(4):453–458

    Article  Google Scholar 

  • Li PY, Qian H, Wu JH (2011). Application of set pair analysis method based on entropy weight in groundwater quality assessment-a case study in Dongsheng City, northwest China. E-J Chem 8(2):851–858

    Article  Google Scholar 

  • Li PY, Wu JH, Qian H, Lyu XH, Liu HW (2014). Origin and assessment of groundwater pollution and associated health risk: a case study in an industrial park, northwest China. Environ Geochem Health 36(4):693–712

    Article  Google Scholar 

  • Li GY, Zhou WF (2006) Impact of karst water on coal mining in North China. Environ Geol 49(3):449–457

    Article  Google Scholar 

  • Li SC, Zhou ZQ, Li LP, Xu ZH, Zhang QQ, Shi SS (2013) Risk assessment of water inrush in karst tunnels based on attribute synthetic evaluation system. Tunn Undergr Sp Tech 38:50–58

    Article  Google Scholar 

  • Li LP, Zhou ZQ, Li SC, Xue YG, Xu ZH, Shi SS (2015) An attribute synthetic evaluation system for risk assessment of floor water inrush in coal mines. Mine Water Environ 34(3):288–294

    Article  Google Scholar 

  • Liu Q (2009) A discussion on water inrush coefficient. Coal Geol Explor 37(4):34–38. doi:10.3969/j.issn.1001-1986.2009.04.009 (In Chinese)

    Google Scholar 

  • Liu TQ, Chen ST, Chen XH (1995) Preliminary study on steeply inclined coal seam mining under water body. J Chin Coal Soc 2(3):1–14 (Chinese)

    Google Scholar 

  • Liu SL, Qiu WH (1998) Studies on the Basic Theories for MADM. Syst Eng Theory Pract 18(1):38–43. doi:10.3321/j.issn:1000-6788.1998.01.007 (In Chinese)

    Google Scholar 

  • Lu YL, Wang LG (2015) Numerical simulation of mining-induced fracture evolution and water flow in coal seam floor above a confined aquifer. Comput Geotech 67:157–171

    Article  Google Scholar 

  • Mandelbrot BB (1983) The Fractal Geometry of Nature. Revised and enlarged edit. W. H. Freeman, New York City

    Google Scholar 

  • Mandelbrot BB (1986a) Self-affine fractal sets, I: the basic fractal dimensions. Fractals in Physics, Proc 6th Trieste International Symp 1:3–15. DOI:10.1016/B978-0-444-86995-1.50004-4

    Google Scholar 

  • Mandelbrot BB (1986b) Self-affine fractal sets, II: length and surface dimensions. Fractals in Physics, Proc 6th Trieste International Symp 1:17–20. doi:10.1016/B978-0-444-86995-1.50005-6

    Google Scholar 

  • Mandelbrot BB (1979) Fractals: Form, Chance and Dimension. WH Freeman, San Francisco

  • Meng ZP, Li GP, Xie XT (2012) A geological assessment method of floor water inrush risk and its application. Eng Geol 143–144:51–60

    Article  Google Scholar 

  • Nguyen QP, Konietzky H, Nguyen QL, Pham NA (2014) Numerical simulation of the influence of water inrush on underground coal mining stability in Vietnam. Mine Planning and Equipment Selection, Springer International, Heidelberg, pp 629–636

    Google Scholar 

  • Núñez JA, Cincotta PM, Wachlin FC (1996) Information entropy: an indicator of chaos. Chaos in gravitational N-body systems (La Plata, 1995). Celest Mech Dyn Astr 64(1–2):43–53

    Article  Google Scholar 

  • Okubo PG, Aki K (1987) Fractal geometry in the San Andreas Fault system. J Geophys Res 92(B1):345–355

    Article  Google Scholar 

  • Pang YH, Wang GF, Ding ZW (2014) Mechanical model of water inrush from coal seam floor based on triaxial seepage experiments. Int J Coal Sci Technol 1(4):428–433

    Article  Google Scholar 

  • Peng SP, Wang JA (2001) Coal mining safety on confined water body. China Coal Industry Publ House, Beijing (In Chinese)

  • Qiu M, Shi LQ, Teng C, Zhou Y (2016) Assessment of water inrush risk using the fuzzy Delphi analytic hierarchy process and grey relational analysis in the Liangzhuang coal mine, China. Mine Water Environ 39:1–12

    Google Scholar 

  • Ribičič MS, Kočevar M, Hoblaj R (1991) Hydrofracturing of rock as a method of evaluation of water, mud and gas inrush hazards in underground coal mining. Proc. 4th International Mine Water Assoc Congr 1:1–12

    Google Scholar 

  • Scholz CH, Aviles CA (1985) Fractal dimension of the 1906 San Andreas Fault and 1915 Pleasant Valley faults. Earthquake. Notes 55(1):20

    Google Scholar 

  • Shi L, Qiu M, Wei W, Xu D, Han J (2014) Water inrush evaluation of coal seam floor by integrating the water inrush coefficient and the information of water abundance. Int J Mining Sci Technol 24(5):677–681

    Article  Google Scholar 

  • Simpson DM, Human RJ (2008) Large-scale vulnerability assessments for natural hazards. Nat Hazards 47(2):143–155

    Article  Google Scholar 

  • Slesarev VD (1948) Design of the Optimal Mine Pillars. Mechanika, Gornoe Delo, Ugletehizdat, Moskow, pp 238–261 [In Russian]

  • State Administration of Coal Mine Safety (2009) Regulations of preventing water hazards for coalmines. Coal Industry Press, Beijing (Chinese)

  • State Administration of Coal Industry (2000) Regulations of the coal pillar design for main roadway and coal mining under buildings, water bodies and railways. Coal Industry Press, Beijing (Chinese)

  • Sun YJ, Xu ZM, Dong QH, Liu SD, Gao RB, Jiang YH (2008) Forecasting water disaster for a coal mine under the Xiaolangdi reservoir. J China Univ Mining Technol 18(4):516–520

    Article  Google Scholar 

  • Wang MY (1977) Mechanism and prediction of water inrush from coal seam floor in the Carboniferous Permian coal field in Hebei, Shandong and Henan. Coal Geol Explor 5:21–32 (In Chinese)

    Google Scholar 

  • Wang LG, Miao XX (2006) Numerical simulation of coal floor fault activation influenced by mining. J China Univ Mining Technol 16(4):385–388

    Article  Google Scholar 

  • Wang LG, Miao XX, Dong X, Wu Y (2008) Application of quantification theory in risk assessment of mine flooding. J China Univ Mining Technol 18(1):38–41

    Article  Google Scholar 

  • Wang JA, Park HD (2003) Coal mining above a confined aquifer. Int J Rock Mech Min 40(4):537–551

    Article  Google Scholar 

  • Wang JA, Tang J, Jiao SH (2015) Seepage prevention of mining-disturbed riverbed. Int J Rock Mech Min 75:1–14

    Google Scholar 

  • Wang LG, Wu Y, Sun J (2009) Three-dimensional numerical simulation on deformation and failure of deep stope floor. P Earth Planetary Sci 1(1):577–584. doi:10.1016/j.proeps.2009.09.092

    Article  Google Scholar 

  • Wang Y, Yang WF, Li M, Liu X (2012) Risk assessment of floor water inrush in coal mines based on secondary fuzzy comprehensive evaluation. Int J Rock Mech Min 52:50–55

    Article  Google Scholar 

  • Wei J, Li Z, Shi L, Guan Y, Yin H (2010) Comprehensive evaluation of water-inrush risk from coal floors. Min Sci Technol 20(1):121–125

    Google Scholar 

  • Wu Q, Fan SK, Zhou WF, Liu SQ (2013) Application of the analytic hierarchy process to assessment of water inrush: a case study for the No. 17 Coal Seam in the Sanhejian Coal Mine, China. Mine Water Environ 32(3):229–238

    Article  Google Scholar 

  • Wu JH, Li PY, Qian H, Chen J (2015) On the sensitivity of entropy weight to sample statistics in assessing water quality: statistical analysis based on large stochastic samples. Environ. Earth Sci 74(3):2185–2195

    Article  Google Scholar 

  • Wu Q, Liu YZ, Liu DH, Zhou WF (2011) Prediction of floor water inrush: The application of GIS-based AHP vulnerable index method to Donghuantuo coal mine, China. Rock Mech Rock Eng 44(5):591–600

    Article  Google Scholar 

  • Wu Q, Zhou WF (2008) Prediction of groundwater inrush into coal mines from aquifers underlying the coal seams in China: vulnerability index method and its construction. Environ Geol 56(2):245–254

    Article  Google Scholar 

  • Wu Q, Xu H, Pang W(2008) GIS and ANN coupling model: an innovative approach to evaluate vulnerability of karst water inrush in coalmines of north China. Environ Geol 54(5):937–943

  • Xu JP, Sui WH, Gui H, Zhang, YD (2009) Utilizing angular displacement to monitor failure of coal seam floor. P Earth Planet Sci 1(1):943–948

    Article  Google Scholar 

  • Xu ZM, Sun YJ, Dong QH, Zhang GW, Li S (2010) Predicting the height of water-flow fractured zone during coal mining under the Xiaolangdi Reservoir. Min Sci Technol (China) 20(3):434–438

    Article  Google Scholar 

  • Xu ZB, Wang JY, Zhang DS, Xie HP (1996) Fractal dimension description of complexity of fault network in coal mines. J China Coal Soci 21(4):358–363 (Chinese)

    Google Scholar 

  • Yao BH, Bai HB, Zhang BY (2012) Numerical simulation on the risk of roof water inrush in Wuyang Coal Mine. Int J Mining Sci Technol 22(2):273–277

    Article  Google Scholar 

  • Yuan R, Li Y, Jiao Z (2015) Movement of overburden stratum and damage evolution of floor stratum during coal mining above aquifers. Proc Eng 102:1857–1866

    Article  Google Scholar 

  • Zadeh LA (1965) Fuzzy sets. Inform Control 8(3):338–353

    Article  Google Scholar 

  • Zhang JC (2005) Investigations of water inrushes from aquifers under coal seams. Int J Rock Mech Min 42(3):350–360

    Article  Google Scholar 

  • Zhang HQ, He YN, Tang CA, Ahmad B, Han LJ (2009) Application of an improved flow-stress-damage model to the criticality assessment of water inrush in a mine: a case study. R Rock Mech Rock Eng 42(6): 911–930

    Article  Google Scholar 

  • Zhu QH, Feng MM, Mao XB (2008) Numerical analysis of water inrush from working-face floor during mining. J China U Min Tech 18(2):159–163

    Article  Google Scholar 

  • Zhu B, Wu Q, Yang J, Cui T (2014) Study of pore pressure change during mining and its application on water inrush prevention: a numerical simulation case in Zhaogezhuang coalmine, China. Environ. Earth Sci 71(5):2115–2132

    Article  Google Scholar 

  • Zou ZH, Yi Y, Sun JN (2006) Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment. J Environ Sci 18(5):1020–1023

    Article  Google Scholar 

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Acknowledgements

The authors acknowledge the financial support from the National Natural Science Foundation of China under Grant 41472268, the 973 Program under Grant 2013CB227903, a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions, and the 111 Project under Grant B14021.

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Authors and Affiliations

  1. School of Resources and Geosciences, State Key Laboratory for Geomechanics and Deep Underground Engineering, China University of Mining and Technology, 1 University Rd, Xuzhou, Jiangsu, 221116, China

    Binbin Yang & Wanghua Sui

  2. Yongcheng Coal and Electricity Holding Group Co. Ltd, Henan Energy and Chemical Industry Group, Middle Guangming Rd, Yongcheng, Henan, 476600, China

    Lihong Duan

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  1. Binbin Yang
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Correspondence to Wanghua Sui.

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Yang, B., Sui, W. & Duan, L. Risk Assessment of Water Inrush in an Underground Coal Mine Based on GIS and Fuzzy Set Theory. Mine Water Environ 36, 617–627 (2017). https://doi.org/10.1007/s10230-017-0457-1

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