Abstract
A new evaluation model, based on fractal theory and an improved analytic hierarchy process (IAHP), was developed to predict the potential for water inrush. Fractal theory was used to quantitatively evaluate the complexity of the fault zones, which is a major water inrush factor. Study of the Lu-an mining area showed that the faults there can be subdivided into four levels of complexity: simple, medium, relatively complex, and complex. The overall complexity of the fault network in the study area was moderate. The IAHP was used to study the potential for coal floor water inrush through these faults. The results indicated that this mining district can be divided into risk-based zones. The extremely high risk zones were mainly located in the northern Tun-liu mine and the northern Chang-cun mine; high risk zones were primarily distributed in the Tun-liu mine and the southwestern Wang-zhuang mine. All other mines were classified as medium and low risk zones.
Zusammenfassung
Ein neues Bewertungsmodell, basierend auf der Fraktal-Theorie und dem Improved Analytic Hierarchy Process (IAHP), wurde entwickelt, um das Potenzial für Wassereinbrüche zu bestimmen. Die Fraktal-Theorie wurde benutzt, um die Komplexität von Störungszonen als Haupteinflussfaktor bei Wassereinbrüchen quantitativ zu bewerten. Untersuchungen des Lu-an-Reviers zeigten, dass die Störungen in 4 Komplexitätskategorien eingeteilt werden können: einfach, mittel, relativ komplex und komplex. Die Gesamtkomplexität des Störungsnetzes im Untersuchungsgebiet war moderat. Der IAHP wurde für die Untersuchung des Potentials von Wassereinbrüchen aus dem Liegenden der Kohle durch diese Störungen benutzt. Die Ergebnisse zeigten, dass dieses Bergbaurevier in Risiko-basierte Zonen eingeteilt werden kann. Die Zonen extrem hohen Risikos befanden sich vorwiegend im nördlichen Tun-liu Bergwerk und im nördlichen Chang-cun Bergwerk. Zonen hohen Risikos lagen vor allem i Tun-liu Bergwerk und im südwestlichen Wang-zhuang Bergwerk. Alle anderen Bergwerke wurden als Zonen mittleren oder niedrigen Risikos.
Resumen
Se desarrolló un modelo nuevo, basado en la teoría fractal y en un proceso analítico jerárquico mejorado (IAHP), para predecir la posibilidad de irrupción de agua. La teoría fractal fue usada para evaluar cuantitativamente la complejidad de la zona de fallas que es el principal factor que afecta la irrupción de agua. El estudio del área minera de Lu-an mostró que las fallas puede ser subdivididas en cuatro niveles de complejidad: simple, media, relativamente compleja y compleja. La complejidad global de la red de fallas en el área de estudio fue moderada. El IAHP fue usado para estudiar la posibilidad de irrupción de agua a través del piso de carbón a través de estas fallas. Los resultados indicaron que el distrito minero puede ser dividido en zonas de acuerdo al riesgo. Las zonas de riesgo extremo fueron principalmente localizadas en las minas Tun-liu y Chang-cun en el norte; las zonas de alto riesgo se distribuyeron en la mina Tun-liu y en la mina Wang-zhuang en el sudoeste. Todas las otras minas fueron clasificadas como zonas de riesgo bajo o medio.
摘要
本文基于分形理论和改进的层次分析法建立了一个煤层底板突水危险性评价模型。采用分形理论定量评价了底板突水的主控因素断层, 结果表明, 潞安矿区断层复杂程度可分为简单、中等、较复杂和复杂4个等级, 断层复杂程度整体上表现为中等。采用改进的层次分析法对潞安矿区煤层底板突水进行了评价分区, 可分为低风险、中等风险、高风险和极高风险四个等级, 其中极高风险区主要分布于常村矿与屯留矿北部, 高风险区主要分布于屯留矿、王庄矿西南部, 其余为中等风险区和低风险区。
Similar content being viewed by others
References
Bez N, Bertrand S (2011) The duality of fractals: roughness and self-similarity. Theor Ecol 4:371–383
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 31:138–146
Feng ZG, Sun XQ (2014) Box-counting dimensions of fractal interpolation surfaces derived from fractal interpolation functions. J Math Anal Appl 412(1):416–425
Fernandez-Martinez M, Sanchez-Granero MA (2014) Fractal dimension for fractal structures. Topol Appl 163:93–111
Han XS, Pan GQ (2013) Three scale AHP method in the application of the mine geological environment assessment—Datong in Shanxi province as an example. Groundwater 35(3):148–153 (In Chinese, with English abstract)
Li JL, Feng Q, Si JH (2008) Fractal study of sustainable proportions of natural and artificial oases. Environ Geol 55(7):1389–1396
Li F, Phoon KK, Du X, Zhang M (2013) Improved AHP method and its application in risk identification. J Constr Eng Manag ASCE 139(3):312–320
Li JL, Zhang HY, Wang XY, Feng YL, Liu Z, Han L (2014) Application and suggestion on vulnerable index method of coal seam floor water burst evaluation. Chin Coal Soc 39(4):725–730 (In Chinese, with English abstract)
Li LP, Zhou ZQ, Li SC (2015a) An attribute synthetic evaluation system for risk assessment of floor water inrush in coal mines. Mine Water Environ 34(3):288–294
Li RZ, Wang Q, Wang XY, Liu XM, Li JL, Zhang YX (2015b) Relationship analysis of the degree of fault complexity and the water irruption rate based on fractal theory. Mine Water Environ. doi:10.1007/s10230-015-0348-2
Liu XL, Wang SY (2012) Mine water inrush forecasting during the mining under waters. Disaster Adv 5(4):876–881
Mandelbrot BB (1977) Fractals: forms, chance and dimension. W.H. Freeman, San Francisco, CA
Mandelbrot BB (1982) The fractal geometry of nature. W.H. Freeman, San Francisco, CA
Saaty TL (2008) Decision-making with the analytic hierarchy process. Int J Serv Sci 70(1):83–98
State Administration of Work Safety of China and State Administration of Coal Mine Safety of China (2009) Provisions for mine water prevention and control. China Coal Industry Publishing House, Beijing (In Chinese)
Wang XY, Li SF, Xu GQ, Zhao YQ, Gao ZJ, Dong DL (2011) Applied Hydrogeology. China University of Mining Press, Xuzhou (In Chinese)
Wang Y, Yang WF, Li M (2012) Risk assessment of floor water inrush in coal mines based on secondary fuzzy comprehensive evaluation. Int J Rock Mech Min 55(52):50–55
Wei JC, Li ZJ, Shi LQ, Guan YZ (2010) Comprehensive evaluation of water-inrush risk from coal floors. Min Sci Technol 20(2010):121–125
Wu Q, Zhang ZL, Ma JF (2007) A new practical methodology of the coal floor water bursting evaluating: the master controlling index system construction. J Chin Coal Soc 32(1):43–47 (In Chinese, with English abstract)
Wu Q, Liu YZ, Liu DH (2011a) 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
Wu Q, Liu YZ, Yang L (2011b) Using the vulnerable index method to assess the likelihood of a water inrush through the floor of a multi-seam coal mine in China. Mine Water Environ 30(1):54–60
Wu Q, Fan SK, Zhou WF (2013) Application of the analytic hierarchy 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
Wu Q, Liu Y, Zhou WF (2015) Evaluation of water inrush vulnerability from aquifers overlying coal seams in the Menkeqing coal mine, China. Mine Water Environ 34(3):258–269
Xiao JY, Tong MM, Jiang CL (2012) Prediction of water inrush quantity from coal floor based on fuzzy evidence theory. J Chin Coal Soc 37(1):131–137 (In Chinese, with English abstract)
Xie QM, Xia YY (2004) A multi-objective decision-making method for the treatment scheme of landslide hazard. J Univ Sci Technol B 11:101–105
Zhang GM, Zhang K, Wang LJ (2015) Mechanism of water inrush and quicksand movement induced by a borehole and measures for prevention and remediation. B Eng Geol Environ 74(4):1395–1405
Acknowledgments
This work was financially supported by the National Natural Science of Foundation of China (Grant 41272250, 41402216) and the Technological Innovation Team of colleges and universities in Henan Province of China (Grant 15IRTSTHN027).
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Wang, X., Wang, T., Wang, Q. et al. Evaluation of Floor Water Inrush based on Fractal Theory and an Improved Analytic Hierarchy Process. Mine Water Environ 36, 87–95 (2017). https://doi.org/10.1007/s10230-016-0407-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10230-016-0407-3