“脆弱性指数法”对灵北煤矿2下煤层底板突水危险性评价

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.     

赵官井田10煤层底板突水危险性评价

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。      

改进脆弱性指数法在煤矿底板突水评价中的应用

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。     

基于改进变权模型的煤层底板突水危险性评价

在目前煤层底板突水评价模型中,变权模型解决了常权模型中权重不变所导致的主控因素指标值被其他指标中和的问题,凸显了主控因素指标值突变的控制作用特征。但变权模型中状态变权函数区间划分不符合正态分布规律,同时,调权参数的确定过于繁琐。针对此,对现有变权模型进行改进,首先将状态变权函数区间由四段式,调整为符合正态分布的三段式,即惩罚区间、不惩罚不激励区间、激励区间。其次,通过分析主控因素指标值归一化累积频率确定变权区间阈值,并分别选取累积频率界限值25%、75%对应值作为各区间的阈值d_j1、d_j2。最后,通过对调权参数赋初值、微调整,确定最终调权参数,从而构建煤层底板突水的变权评价模型。以三交煤矿5号煤层为例,应用改进的分区变权评价模型对目标煤层底板突水脆弱性进行评价,并与常权评价模型评价结果进行对比分析,发现突水危险区整体分布趋势一致,但局部断层突变处存在明显差异,表明变权模型有效凸显了断层对突水的控制作用,较好地刻画区域底板突水情况,较符合实际。     

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

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。      

基于GIS的改进AHP型脆弱性指数法

AHP法是煤层底板突水预测预报的关键技术之一,但传统基于“1~9”标度的AHP法往往存在一致性效果不够理想等问题.通过对AHP法的改进研究,提出了基于“10/10~18/2”标度的改进AHP法型脆弱性指数法评价技术.以成庄矿3#、9#和15#煤层底板奥灰突水脆弱性评价为例,在建立各主控因素专题层图基础上,应用基于“10/10~18/2”新标度的改进AHP法,确定了各主控因素的权重;进一步建立了煤层底板奥灰突水的脆弱性评价模型,得出了各煤层脆弱性评价分区.研究表明,改进的AHP法构建的判断矩阵具有较好的一致性;通过与传统突水系数法评价结果对比可知,基于GIS的改进AHP型脆弱性指数法评价能够真实反映多因素影响下煤层底板突水的非线性动力过程,评价结果更为吻合实际.      

聚类分析模糊综合评判法在矿井突水危险性评价预测中的应用

为了准确评价矿井突水危险性,根据聚类分析和模糊综合评判法的原理,以大同矿区同地永财坡煤矿为例,针对现有9个钻孔的煤层底板破坏深度、底板保护层深度、奥灰静水水压、底板有效保护层深度、带压系数、突水系数6个影响矿井突水的关键因子,在采用聚类分析法对该煤矿4#煤层底板突水进行分区的基础上,再利用模糊综合评判法对各突水分区进行等级划分,将突水分区划分成"安全"、"较安全"、"较危险"、"危险"和"极危险"5个等级。经计算,该矿4#煤层底板北部及中部划分为安全区,仅南部和东南部为突水较危险和极危险区。     

基于EW-FAHP的煤层底板承压水突水危险评价

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。     

淮北袁店煤矿101、102采区煤层底板突水危险性综合评价

为有效控制煤层底板带压开采突水发生,同时解决突水系数法评价底板突水的局限性,引入灰色模糊聚类法综合评价煤层底板突水危险性。以袁店煤矿101、102采区为例,通过对10煤层水文地质条件、底板充水水源和充水通道深入分析,提取评价煤层底板突水危险性关键指标,综合考虑岩溶裂隙发育、地质构造、隔水层厚度、裂隙含水层富水性、灰岩含水层厚度5个突水主控因素,并进行底板突水危险性分区。结果表明：101采区底板突水危险性较小,102采区危险性较大。建议对102采区局部富水地段进行注浆加固,以达到防治突水的目的。     

基于GIS和AHP的谢桥煤矿13-1煤顶板突水危险性评价

为解决谢桥矿13-1煤层顶板突水评价难题,利用ArcGIS的空间分析功能,通过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方法确定各主控因素的权重比例,在此基础上将各个主控因素进行无量纲处理后按照权重进行复合叠置,提出煤层顶板突水危险性的分区方案。将顶板已有出（突）水数据与分区结果比较,结果表明,线性脆弱性指数法可以客观、定量、准确的评价煤层顶板突水危险性。      

Application on Floor Water Inrush Evaluation Based on AHP Variation Coefficient Method with GIS

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.     

基于matlab的煤层底板突水预测系统

针对当前煤层底板突水预测存在的问题,在突水概率指数法预测预报系统的基础上,用matlab开发出了一套新型煤层底板突水预测系统软件。通过对地质、水文地质等信息数据进行分析处理,从而确定导致煤层底板突水的主控因素及次级影响因素,并分别赋予其相应的权重值,将各因素在底板突水中所起的作用定量化。特别是对于不同矿区不同控制因素的影响,其相应权重值的大小可以灵活改变。建立赋权求和数学模型,绘制出各个主要控制因素的专题图,并根据各个主要控制因素的不同权重值,叠合绘制出底板突水概率指数法突水分区图。同时计算出煤层底板突水概率指数。将系统软件应用于工程实际,预测效果与实际情况相吻合。      

A GIS-based method of risk assessment on no. 11 coal-floor water inrush from Ordovician limestone in Hancheng mining area,China

The no. 11 coal seam in the deep area of Hancheng mining area is mining in recent years, which is threatened by the water inrush from the Ordovician limestone aquifer. Coal-floor water inrush is governed by the water abundance of coal-floor aquifer, the water-resisting performance of coal-floor aquitard, and the pathway connecting the water source and the working face. To make an accuracy risk assessment of water inrush from the no. 11 coal seam floor, a GIS-based vulnerability index method (VIM) is adopted for its superior comprehensive consideration of more controlling factors, powerful spatial analysis, and intuitively display functions. This study firstly established an index system including the water pressure of the coal-floor aquifer, the unit water inflow, the thickness, the core recovery percentage, the thickness ratio of brittle rocks to ductile rocks, the thickness of effective aquitard, and the accumulated length of faults and folds, of which the former six indexes governed the water abundance of the coal-floor aquifer which was combined with the last two factors to determine the risk of coal-floor water inrush. Secondly, the thematic map of each controlling factor is established by GIS using the geological prospecting data, and the weight of each factor is determined by the analytic hierarchy process (AHP) after consulting the expert review panel. At last, a vulnerability index is obtained and used to assess the risk of coal-floor water inrush of the no. 11 coal seam. The risk of water inrush of the no. 11 coal seam of the study area was ranked to three zones: the southeastern shallow area in red color is the dangerous zone, the wide northwestern area in green color is the safe zone, and the transition area in yellow color is the moderate-risk zone. Compared with the actual water-inrush incidents, the risk assessment result was verified to achieve an accuracy of 82.35%, which is proved to be a dependable reference for the prevention and controlling of coal-floor water inrush of the no. 11 coal seam in Hancheng mining area.     

Assessment of water inrush risk using the principal component logistic regression model in the Pandao coal mine,China

In order to improve the accuracy of floor water inrush assessment, the risk prediction model of floor water inrush was established by combining the principal component logistic regression analysis (PCLRA) and GIS spatial geographic analysis. In this paper, the geological data of Pandao coal mine was taken as the engineering background. First of all, main controlling factors of floor water inrush were determined and quantified. Next, PCLRA was used to determine the weight of each factor and establish the mathematical model for predicting the floor water inrush. And then, GIS’s spatial analysis and data processing function was used to draw related single factor thematic maps. Related thematic maps were weighted superposed to draw a floor water inrush zoning map based on PCLRA mathematical model. The study areas were divided into five levels by Jenks optimization method and vulnerability index initial model. And the corresponding threshold range was determined. The results show that (1) the high sensitivity factors in floor failure depth were added to evaluate the water inrush, and the fault fractal dimension was used to replace the fault structure related factors, and the main controlling factors of floor water inrush are more comprehensive; (2) the fitting degree of PCLRA model is high and the test accuracy is 83.3%; (3) the prediction results were well fitted to the actual position of water inrush (three water inrush points are located in the dangerous area, and two water inrush points are located in the relatively dangerous area).     

Assessment of water inrush and factor sensitivity analysis in an amalgamated coal mine in China

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.     

基于GIS的煤层底板突水脆弱性评价——以山西曹村井田为例

煤层底板突水因素众多,突水系数法作为传统的方法所能考虑的突水影响因素种类很有限,不能全面的描述煤层底板突水的复杂机理。为保障煤矿的安全生产,本文以底板突水脆弱性理论为基础,对曹村井田II^#煤层底板突水危险性进行评价,为煤矿今后的安全生产起指导作用。