共查询到15条相似文献，搜索用时 171 毫秒
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从地质构造、含水层、隔水层、开采条件等方面详细分析了赵官井田10煤层底板突水的影响因素,确定了断层强度指数、褶皱分维值、"底板充水含水层组"水压、"底板充水含水层组"富水性、奥灰富水性、隔水层厚度、泥岩比率、底板破坏深度8个主控因素作为10煤层底板突水危险性评价的决策指标,并建立了各主控因素专题图;运用层次分析法(AHP)确定了各主控因素的权重系数,建立了基于"脆弱性指数法"的底板突水危险性评价模型,对10煤层底板突水危险性进行了定量评价,结果表明:在井田的南部煤层露头处脆弱性指数小,突水可能性较小;在井田的北部,特别是在井田东北部,脆弱性指数大,突水危险性较大。 相似文献
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GIS的AHP型脆弱性指数法在李雅庄矿底板突水评价中的应用 总被引：2，自引：0，他引：2
山西霍州矿区李雅庄煤矿石炭系太原组K2灰岩岩溶发育,加之区内断裂构造发育,水文地质条件较为复杂。为解决上组2号煤底板太灰突水评价难题,采用GIS的AHP型脆弱性指数法,首先建立煤层底板突水主控因素体系,并通过GIS对主控因素数据进行采集及归一化处理,建立子专题图层,然后运用AHP法确定各主控因素的权重比例,提出煤层底板突水脆弱性的分区方案。与传统突水系数法相比,脆弱性指数法能较为全面地反映不同区域的相对脆弱关系,其评价结果更实际、可靠。 相似文献
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针对传统的AHP型脆弱性指数法在权重确定方面的不足,采用熵权法对其改进,将熵权法计算的客观权重与AHP法计算的主观权重进行加权平均,综合确定各主控因素诱发突水的权重比例。在综合分析长平煤矿水文地质资料的基础上,应用GIS建立主控因素专题图并进行归一化处理,运用基于GIS的改进AHP型脆弱性指数法确定各主控因素权重,建立井田西部3号煤底板奥灰突水危险性评价模型。利用自然间断点分级法确定了分区阈值,将研究区按突水危险性的相对大小分为5个区域。评价结果符合实际,对煤矿安全生产具有重要的现实意义。 相似文献
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在分析矿井地质及水文地质条件的基础上,采用脆弱性指数法对灵北煤矿2下煤层底板突水进行评价,运用AHP确定底板突水各主控因素的权重,建立煤层底板突水脆弱性模型,将研究区分为相对安全区、较安全区、过渡区、较脆弱区、脆弱区五个区.相对于传统突水系数法,脆弱性指数法评价更能全面分析研究各区域不同的脆弱性,有针对性地制定防治水对策措施与建议,对煤矿安全生产更具有指导意义. 相似文献
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为克服层次分析法主观确权的弊端,同时避免熵权客观确权与主控因素实际重要程度相悖的错误,以山西长治三元煤矿3号煤层底板奥灰突水危险性评价为例,将熵权与层次分析耦合确定煤层底板突水主控因素权重并建立脆弱性指数模型,采用K均值聚类法对脆弱性指数值进行聚类分区,确定阈值3个,按照突水危险程度将研究区分为安全区、相对安全区、过渡区和危险区4个区域。经对比验证评价结果符合实际情况。 相似文献
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新阳矿9-10-11号煤层底板低于奥灰岩溶水位,承受水压较高,存在带压开采问题。依据矿区水文地质勘查资料,通过对9-10-11号煤层底板隔水岩层隔水性能、奥灰岩溶水富水程度、底板断裂构造发育情况、煤层底板承压大小以及采煤扰动底板破坏深度等突水因素分析,表明井田西南部断裂构造发育地段为突水危险区。分别采用突水系数法和突水危险度法对全井田9-10-11号煤层底板突水危险性进行评价,评价结果显示井田南部及断裂构造发育地段为突水危险区。理论分析与定量评价结果基本一致。针对9-10-11号煤层底板突水安全评价结果,提出了相应的防突水对策。 相似文献
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《中国煤炭地质》2017,(10)
焦家寨煤矿主采石炭系太原组2#、5#煤层,煤层底板奥灰承压含水层是矿井防治的重点。本矿虽未发生过奥灰承压水突水,但其相邻矿井曾发生过奥灰突水事故。目前煤矿回采标高最低的工作面为太原组下部的5#煤层52108工作面的突水系数值为0.056~0.063 MPa/m,在局部煤层底板构造裂隙发育的区域存在突水风险。选择音频电穿透、直流电测深和无线电波透视三种物探方法,对工作面底板的富水性及隐伏构造的发育情况进行了探测,采用钻探手段对物探异常区进行了有针对性验证,结果表明,探查区域不存在导水构造,工作面回风巷1号、2号、3号出水点与奥灰承压水无水力联系;工作面底板隔水层比较完整,具有较好的隔水性能。该结论已被工作面回采所证实。 相似文献
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The prediction and prevention of floor water inrush is directly related to the safety of the coal mine production. The previous evaluation method of floor water inrush was more one-sided and lacked main control factors related to mining conditions. In order to evaluate the floor water inrush more accurately, under the project background of geological data of Wanglou coal mine, stope width, mining depth, fault scale index, water pressure, water abundance and thickness of aquifer were selected as main controlling factors of floor water inrush. Combined with the subjective weight analytical hierarchy process and the objective weight variation coefficient method, the weight coefficients corresponding to the main controlling factors were obtained respectively. The thematic map of the risk assessment of coal seam floor water inrush was drawn by combining the constructed comprehensive weight vulnerability index model and geographic information system. The results show that: ① according to the actual geological data of mine, two fault related factors were removed. And stope width and mining depth were increased as the main controlling factors to evaluate floor water inrush. It is easier to compare and calculate the weight of evaluation factors. ② The constructed comprehensive weight vulnerability index model can comprehensively evaluate the risk of floor water inrush. And the results of the evaluation are more accurate. ③ The related thematic maps can directly reflect the risk of floor water inrush, which is of guiding significance for the prediction and prevention of coal seam floor water inrush. 相似文献
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Hydrogeological data are generally incomplete and inaccurate in amalgamated coal mines in China, which results in inaccuracy in water inrush forecasts. To enhance the precision of the prediction of water inrush from coal floor in an amalgamated coal mine, the vulnerability index method was developed using an analytic hierarchy process (AHP) to analyze the water inrush hazard. Six factors related to water inrush were selected and the corresponding single factor thematic map was established through geographic information system (GIS). The AHP model was built to calculate the weight of each factor. The final forecast map based on vulnerability index was acquired by superposing the six thematic maps. The forecast map was consistent with the real water inrush position. The sensitivity of the six factors was analyzed and the water-resisting layer played a significant role in controlling water inrush. Several suggestions about water inrush prevention were put forward based on the prediction results. 相似文献
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煤层深部开采使得煤矿底板水害事故频发,传统突水危险性评价方法评价指标单一、评价结果偏离实际的弊端逐渐显露,造成众多新型评价方法涌现。以河北省华北型煤田东欢坨矿为研究对象,选取含水层性能、隔水层性能、地质条件、煤层条件的评价因素集,综合考虑10个评价因素,建立适用于东欢坨矿的底板突水危险性评价指标体系;利用层次分析法确定各指标主观权重,利用CRITIC法确定各指标客观权重,将2者耦合得到综合权重,兼顾专家主观经验与数据客观信息,保证权重确定的全面性;引入加权秩和比法,构建评价矩阵,依据指标对评价对象所产生的优劣性影响将其分为高优型指标和低优型指标,编秩计算WRSR值,对数据进行分档排序,确定安全、较安全、较危险、危险4个评价等级区间,形成评价模型;利用GIS强大的空间管理及信息处理功能,完成结果的信息展示;将评价结果与实际工程出水位置相比较,发现突水位置都在底板突水较危险区域,并与传统评价方法突水系数法相对比,证明评价模型有效。研究成果形成了煤层底板突水危险性评价新方法,丰富煤层底板突水危险性评价方法的种类,为煤矿防治水工作者提供新思路。 相似文献
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以平顶山十三矿己四采区底板灰岩的突水危险性评价为例,将熵权法(EW)和模糊层次分析法（FAHP）耦合在一起,确定了突水影响因素的权重,并建立了突水危险性评价模型。结果显示:十三矿己四采区二1煤底板标高-150~-350 m区域,不受底板灰岩水的影响,属于安全区;标高-350~-700 m 且不受断层影响的区域属于较安全区;标高-700 m以下及标高-350~-700 m且受断层影响的区域属于突水危险区。在前期突水资料少和数据量有限的条件下,EW-FAHP法能够较为客观地确定突水影响因素权重。 相似文献
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Prediction of Floor Water Inrush: The Application of GIS-Based AHP Vulnerable Index Method to Donghuantuo Coal Mine,China 总被引：6，自引：0，他引：6
Qiang Wu Yuanzhang Liu Donghai Liu Wanfang Zhou 《Rock Mechanics and Rock Engineering》2011,44(5):591-600
Floor water inrush represents a geohazard that can pose significant threat to safe operations for instance in coal mines in
China and elsewhere. Its occurrence is controlled by many factors, and the processes are often not amenable to mathematical
expressions. To evaluate the water inrush risk, the paper proposes the vulnerability index approach by coupling the analytic
hierarchy process (AHP) and geographic information system (GIS). The detailed procedures of using this innovative approach
are shown in a case study in China (Donghuantuo Coal Mine). The powerful spatial data analysis functions of GIS was used to
establish the thematic layer of each of the six factors that control the water inrush, and the contribution weights of each
factor was determined with the AHP method. The established AHP evaluation model was used to determine the threshold value
for each risk level with a histogram of the water inrush vulnerability index. As a result, the mine area was divided into
five regions with different vulnerability levels which served as general guidelines for the mine operations. The prediction
results were further corroborated with the actual mining data, and the evaluation result is satisfactory. 相似文献