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1.
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
2.
Ground water inrush from underlying coal seam aquifers is a serious geohazard during coal mining in China. In order to effectively predict coal floor water inrush, the evaluation index system and evaluation standard for coal floor water inrush, containing quantitative indexes and qualitative indexes, is established on the base of conditions of aquifer and aquiclude, geologic structure and mining disturbance. Simultaneously, grey relational analysis and analytic hierarchy process are used to establish an evaluation model which efficiently overcomes the uncertainty between indexes of water inrush effects and really reflects the degree of importance for each index of water inrush effects. The model is applied to the typical working face of Yuzhou coalfield in the north of China to demonstrate the evaluation process. Compared to the water inrush coefficient method which is widely used for evaluating coal floor water inrush, the presented evaluation model in this paper accords more with the susceptibility of coal floor water inrush by multi-factor and is of nonlinear dynamic characteristics of highly complicated formation mechanism. This method offers a new tool in the assessment of ground water inrush in mine. 相似文献
3.
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
4.
Groundwater inrushes often occur in the coal mines of China. One of the water sources is the aquifers underlying the coal
seams. Because such a water hazard is affected by many factors, data collected from various sources need to be evaluated to
predict its occurrence. This paper introduces an innovative approach in which the water inrush risk is represented by the
vulnerability index. This method combines the geographic information system and the artificial neural network. The artificial
neural network is used to estimate the weight of each factor. Unlike the traditional prediction method in which two controlling
factors are often evaluated without regard to their relative importance, this new approach incorporates multi-factors and
describes the non-linear dynamical processes. 相似文献
5.
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
6.
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. 相似文献
7.
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
8.
华北煤田煤系地层的底部为含水丰富的奥陶系灰岩,该层灰岩与地表水系和煤系地层含水层存在着密切的水力联系。许多大型突水是采掘空间与含水层之间形成突水通道引起的。因此,分析开采工过程中底板岩体中含承压水裂隙的断裂力学特性具有重要意义。本文采用作者提出的数值方法分析了含高压水裂隙在开采过程中的断裂力学特性。假设裂隙面上作用着均匀水压力,考虑地应力的影响,采用断裂力学的叠加原理,分析了采煤工作面推进过程中含承压水裂隙的断裂力学特性,讨论了开采过程中底板承压水导升。结果表明:在工作面推进过程中,位于底板岩层且与含承压水岩层连通的裂隙,会在承压水水压力和扰动应力的共同作用下,产生破坏,导水裂隙带的高度会增加;这就增加了底板突水的危险性。 相似文献
9.
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
10.
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
11.
Mining-induced water inrush is a sudden and destructive underground disaster caused by a mining disturbance. This disaster occurs frequently in the northern region of Shaanxi province in China due to overburden fractures in shallow seam mining, which pose a great threat to residents’ safety. It is therefore essential to construct an accurate prediction model. This study first applies selection hierarchy analysis to the main controlling factors of roof water inrush to study their weights using an analytic hierarchy process (AHP) including five factors: surface water catchment features, wateriness of the aquifer, water-resistant characteristics of aquiclude, combined influence of overburden, and mining disturbance characteristics. The grey relational analysis (GRA) method is used to calculate the correlation degree of each water inrush. The AHP-GRA method presents a comprehensive evaluative model combining the advantages of both approaches to analyze mining safety. Qualitative and quantitative indicators of the roof water inrush prediction model in shallow seam mining are established. Secondly, risk prediction of roof water inrush points and comprehensive water inrush is determined using engineering examples from the Hanjiawan coal mine. Results indicate that during safety mining, water inflow data are consistent with our prediction, thereby substantiating the model’s accuracy and providing a new method for predicting roof water inrush in shallow seam mining. 相似文献
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13.
A DRASTIC-model method based on a geographic information system (GIS) was used to study groundwater vulnerability in Egirdir Lake basin (Isparta, Turkey), an alluvial area that has suffered agricultural pollution. ‘Lineament’ and ‘land use’ were added to the DRASTIC parameters, and an analytic hierarchy process (AHP) method determined the rating coefficients of each parameter. The effect of lineament and land-use parameters on the resulting vulnerability maps was determined with a single-parameter sensitivity analysis. Of the DRASTIC parameters, land use affects the aquifer vulnerability map most and lineament affects it least, after topography. A simple linear regression analysis assessed the statistical relation between groundwater nitrate concentration and the aquifer vulnerability areas; the highest R 2 value was obtained with the modified-DRASTIC-AHP method. The DRASTIC vulnerability map shows that only the shoreline of Egirdir Lake and the alluvium units have high contamination potential. In this respect, the modified DRASTIC vulnerability map is quite similar. According to the modified-DRASTIC-AHP method, the lakeshore areas of Senirkent-Uluborlu and Hoyran plains, and all of the Yalvaç-Gelendost plain, have high contamination potential. Analyses confirm that groundwater nitrate content is high in these areas. By comparison, the modified-DRASTIC-AHP method has provided more valid results. 相似文献
14.
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). 相似文献
15.
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. 相似文献
16.
Suburban areas have become rapid development zones during China’s current urbanization. Generally, these areas are also regional precipitation centers that are prone to flood disasters. Therefore, it is important to assess the flood risk in suburban areas. In this study, flood risk was defined as the product of hazard and vulnerability based on disaster risk theory. A risk assessment index system was established, and the analytic hierarchy process method was used to determine the index weight. The Fangshan District in Beijing, China, which is an example of a typical suburban area undergoing rapid urbanization, was selected for this study. Six factors were considered in relation to hazard, and three factors were considered for vulnerability. Each indicator was discretized, standardized, weighted, and then combined to obtain the final flood risk map in a geographical information system environment. The results showed that the high and very high risk zones in the Fangshan District were primarily concentrated on Yingfeng Street, Xingcheng Street, Xincheng Street, and Chengguanzhen Street. The comparison to an actual flood disaster suggested that the method was effective and practical. The method can quantitatively reflect the relative magnitude and spatial distribution patterns of flood risk in a region. The method can be applied easily to most suburban areas in China for land use planning and flood risk management. 相似文献
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18.
刘桥二矿在开采4煤过程中，七含突水次数达38次之多，严重影响煤矿安全生产。文章在系统地分析刘桥二矿七含涌突水概况的基础上，提出了该矿七含涌突水的主要机理为断裂构造的控制作用和矿山压力的促进作用；指出了砂岩含水层的裂隙发育程度和富水性强弱、煤层的厚度、断层的作用以及4煤与含水层之间隔水层厚度的大小等，是影响工作面涌水的主要因素。研究结果对煤矿砂岩水害的有效防治具有重要的指导意义。 相似文献
19.
Groundwater inrush is a geohazard that can significantly impact safe operations of the coal mines in China. Its occurrence
is controlled by many factors and processes are often not amenable to mathematical expressions. To evaluate the water inrush
risk, Professor Wu and his colleagues have proposed the vulnerability index approach by coupling the artificial neural network
(ANN) and geographic information system (GIS). The detailed procedures of using this innovative approach are shown in a case
study. Firstly, the powerful spatial data analysis functions of GIS was used to establish the thematic layer of each of the
main factors that control the water inrush, and then to choose the training sample on the thematic layer with the ANN-BP Arithmetic.
Secondly, the ANN evaluation model of the water inrush was established 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 four regions with different
vulnerability levels and they served as the general guidelines for the mine operations. 相似文献
20.
为了研究以煤层顶板弱富水含水层为直接充水水源的顶板透水机理,并探索防治方法,以宁夏宁东煤田红柳煤矿1121工作面开采期间发生的4次大规模透水为切入点,通过理论分析、数值模拟并结合井下钻探等工程技术手段,得出该工作面透水是由煤层开采后顶板岩移形成的次生离层水体引发,提出了煤层顶板覆岩中隔水关键层是造成次生离层水体透水的必要条件;研究了隔水关键层位置、尺寸及其水理性质对次生离层水体周期性透水的控制作用;确定了临界隔水关键层厚度为18 m,并提出了次生离层水体致灾前疏放的最佳时机为次生离层水体形成且周期垮落前,最佳位置垂向上为煤层A主隔水关键层顶板,平面上位于下顺槽距煤帮1/6~1/3工作面斜长范围。 相似文献