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.     

Using random forest for the risk assessment of coal-floor water inrush in Panjiayao Coal Mine,northern China

Coal-floor water-inrush incidents account for a large proportion of coal mine disasters in northern China, and accurate risk assessment is crucial for safe coal production. A novel and promising assessment model for water inrush is proposed based on random forest (RF), which is a powerful intelligent machine-learning algorithm. RF has considerable advantages, including high classification accuracy and the capability to evaluate the importance of variables; in particularly, it is robust in dealing with the complicated and non-linear problems inherent in risk assessment. In this study, the proposed model is applied to Panjiayao Coal Mine, northern China. Eight factors were selected as evaluation indices according to systematic analysis of the geological conditions and a field survey of the study area. Risk assessment maps were generated based on RF, and the probabilistic neural network (PNN) model was also used for risk assessment as a comparison. The results demonstrate that the two methods are consistent in the risk assessment of water inrush at the mine, and RF shows a better performance compared to PNN with an overall accuracy higher by 6.67%. It is concluded that RF is more practicable to assess the water-inrush risk than PNN. The presented method will be helpful in avoiding water inrush and also can be extended to various engineering applications.     

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。     

基于组合赋权的加权秩和比法的底板突水危险性评价

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。      

基于GIS和水质水温的矿井突水水源快速判别

针对淮南潘谢矿区新生界下含松散孔隙水与石炭系太原组石灰岩岩溶裂隙水水质接近的特殊情况,提出了基于GIS和水质水温的矿井突水水源快速判别方法。该法是利用测温钻孔的温度-深度拟合结果,构建基于GIS的利用水温识别突水水源的模型,并将其判别结果与基于水质的模糊综合评判计算的结果相结合,综合判别矿井突水水源。本法应用于潘一煤矿86-1号突水判别,实例结果显示,该法可以较好地适用于水质判别效果不佳,而含水层之间存在较大的地温差(埋深差)情况下的突水水源识别。     

Prediction of Floor Water Inrush: The Application of GIS-Based AHP Vulnerable Index Method to Donghuantuo Coal Mine,China

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.     

Using numerical simulation for the prediction of mine dewatering from a karst water system underlying the coal seam in the Yuxian Basin,Northern China

Water inrush from a karst aquifer threatens mine safety in North China because of the special hydrogeological conditions. This paper systematically analyzes the regional hydrogeological conditions of the Cambrian–Ordovician limestone karst aquifer in the Yuxian Basin. Conceptual and mathematical models of karst water flow system are established, and the karst water flow system is simulated by the finite-difference method. The numerical model is checked using hydraulic head from karst water observation holes, and the sensitivity of hydrogeological parameters is analyzed. Further, the risk of water inrush from the karst aquifer underlying the coal seam in the second mining area of the Beiyangzhuang Mine in the basin is evaluated by the water inrush coefficient method. Based on the critical hydraulic head for mining safety, the rate of mine dewatering is simulated for the three stages of the mining plan with the numerical model. The results show that the risk of water inrush in the second mining area is high. The rate of dewatering in the three stages without grouting is 1300, 1860, and 2050 m³/h, respectively, and with local grouting is 1020, 1550, and 1700 m³/h, respectively. Dewatering combined with grouting not only ensures coal mine safety, but also significantly reduces the rate of dewatering. The prediction method of mine dewatering has practical significance in engineering applications.     

煤层底板突水突变模型

本文建立了煤层底板突水的一个尖点突变 (cusp)模型 ,并分析了煤层底板失稳破坏发生突水的机制。基于定态曲面方程 ,可求得煤层底板水压应力比 Ip。当 Ip 1时 ,发生突水 ;当 Ip 1时 ,不会发生突水。基于分支曲线方程 ,可求得煤层底板突水临界采动导水裂隙带深度 h1l,当 h1 h1l 时 ,发生突水 ;当 h1 h1l 时 ,不会发生突水。     

国家庄矿-210m北大巷突水原因分析

肥城矿区国家庄煤矿-210 m北大巷曾发生突水量高达32 970 m3/h的突水事件,出水点附近地质构造复杂,含水层互相对口接触,这一大型突水是承压水沿断裂构造薄弱带突入巷道所致。      

华北型煤矿垂向越导突水特征分析

在对焦作矿区大量突水事例分析的基础上,建立了“越导突水”的概念模型,并从这一模型展开讨论了由断层、密集型裂隙和陷落柱等构造形成的超导突水的8项特征,从而为研究华北型煤矿垂向越导突水实质奠定了基础。     

矿井水情监测与水害风险预警平台设计与实现

任何矿井水害事故均会显现不同的预兆,为夯实水害智能预警基础,明晰了感知、辨识、评估、预测及相互逻辑关系的系统建设内涵,针对不同水害类型,根据其突水机理不同,设计三大类多模式水害典型场景,建立相应突水判据,提出了确定性理论精确预测与包括大数据及深度学习在内的非确定性趋势推测两类预测方法,为智能预警系统的预测预报、预警准则及阈值设置奠定理论基础。以陕西省彬长矿区亭南矿为例,建立了动态信息、静态信息及关联信息的指标体系,将地面水文动态监测单元、井下水情环境监测单元以及采掘工作面采动动态监测单元集成,构建原位采集和突水要素预兆感知系统,实施基于关键层电性参数动态监测、关键部位单点或多点多参数监测联合布置的突水前兆信息精准获取方案,采用确定性模拟模型和非确定性智能模型,实现水害预测预警功能,基于多源数据融合和空间联动分析技术,预警系统实现了井上下全空间水害风险预警“一张图”的可视化展示。实践表明,监测预警平台理论基础扎实,预测预警效果显著。     

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).     

矿井煤层底板突水预测新方法研究

本文针对煤矿矿井煤层底板突水系统为一非线性系统的特性,提出采用对非线性问题具有良好适用性的人工神经网络系统（以下简称神经网络）,进行煤层底板突水预测。以作者们研制,使用神经网络的实践为基础,阐述系统、建模方法、适用条件和应用问题,并在焦作矿务局演马庄矿、焦作金科尔集团方庄煤矿对所建立的煤层底板突水预测神经网络进行生产性检验,取得良好的结果,说明该系统应用于煤层底板突水预测的可靠性。     

基于SSA优化的GA-BP神经网络煤层底板突水预测模型与应用

随煤层开采深度的不断增加,煤矿生产过程中面临着复杂的突水机理和多变的突水主控因素,且各因素间相互联系的不确定性,使底板突水预测的难度不断增加。为准确预测底板突水危险性,针对底板突水的小样本、非线性问题,首先利用遗传算法(Genetic Algorithm,GA)将网络随机赋值的初始权值和阈值初次优化,再选取搜索能力强、稳定性较好的麻雀搜索算法(Sparrow Search Algorithm,SSA)对权值和阈值进行二次寻优,从而建立SSA-GA-BP神经网络底板突水预测模型。分析整理山东省滨湖煤矿地质及水文地质资料,选取含水层水压、含水层厚度、隔水层厚度、断层密度、断层分维值、渗透系数、单位涌水量、底板破坏深度共8个因素,作为预测底板突水的主控因素,绘制各主控因素3D映射投影曲面图;利用Surfer软件中的克里金插值法提取50个数据点作为模型的输入样本(分为训练集40个,测试集10个),对模型进行训练学习,训练误差精度达到要求后,对滨湖煤矿3个未开采工作面的12个数据点进行突水危险性预测。为了验证所建模型的准确性,利用BP、GA-BP、SSA-GA-BP这3种模型对测试集进行预测;为避免模型仅与BP网络预测对比的片面性,同时选取以熵权法确定权重的模糊综合评判法对测试集进行预测;将各网络模型及方法的预测结果与实际值进行对比分析。结果表明:基于SSA优化的GA-BP神经网络模型突水预测误差较小,预测结果准确率更高,为矿井水害预测预报提供了科学的评价方法和理论依据。      

Experimental investigation of fracture propagation and inrush characteristics in tunnel construction

It is well known that water inrush during excavation is one of the greatest challenges in modern underground engineering. However, the fracture propagation and inrush characteristics induced by excavation and high-pressure water are poorly understood due to the lack of an appropriate experimental apparatus and an online and real-time monitoring approach. Accordingly, a model test system for the simulation of water inrush during excavation and water injection was developed. Acoustic emission (AE) monitoring during excavation and injection was used to investigate the fracture propagation and water-inrush channel formation in the host rock. Three distinct stages were observed in the AEs over time and were related to the fracture propagation during excavation and injection, namely fracture initiation, fracture extension, and unstable fracture growth (fracture network). The AE results exhibited an increase in AE activities and changes in the AE spatial correlation during the excavation and during the increase in injection pressure. A comparison of photographs of the water-inrush locations and the mechanical characteristics obtained from the AE test verified the proposed method. The results provide valuable insights and a suitable method for the investigation of the mechanism of water inrush in underground engineering.

     

Spatiotemporal development of mine water inrush and its mechanism—a case study in Ganhe coal mine,Shanxi, China

Mine water inrush is one of the main hazards in coal mining industry. The mechanism and the processes are complex. Investigation of the spatiotemporal development of the hydrological process could lead to a better understanding of mine water inrush and effective countermeasures. For this reason, we investigated spatial and temporal characteristics (i.e., the changes of flow rate, groundwater level, and water quality) during a water inrush event in China, which had a flow rate of 730 m³/h at maximum and 300m³/h under a steady condition. The result shows that the water inrush developed in several stages. A mathematical model of the dynamic change between the water table and the inrush flow rate was constructed. Based on this model, we found the relationship of highly conductive flow channels between some observation boreholes and the water inrush point. In addition, the recharge velocity of the highly conductive flow channels and the equivalent mean flow velocity of the whole mine were determined. A comprehensive analysis of geological, hydrodynamic, and crustal stress conditions was conducted to study the development of the water channel near the F₁₃ fault and the nonlinear process from seepage stage to inrush stage. The result reveals the water inrush is likely caused by activation of faults under combined influences of high crustal stress and high hydraulic pressure.     

深埋特长隧道的突涌水危险性评价研究

为评价隧道突涌水风险,确保施工安全,本文结合工程实例,利用层次分析法和模糊理论构建了隧道突涌水危险性评价模型,并利用P×C分级法确定隧道突涌水危险性等级。实例检验表明：该模型的权值求解方法具操作简单、准确性高等优点,能有效通过一致性检验,且隶属度求解过程有效综合了定性分析与定量评价,保证了分析结果的准确性;同时,该评价模型可定量评价隧道突涌水的危险性等级,且判别结果与现场实测值的判别结果具较好的一致性,验证了该评价模型的可靠性和准确性,为隧道突涌水危险性评估提供了一种有效途径。     

Prediction of groundwater inrush into coal mines from aquifers underlying the coal seams in China: application of vulnerability index method to Zhangcun Coal Mine,China

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.     

Research Status and Development Trends of Mine Floor Water Inrush Grade Prediction

According to the characteristics of mine floor water inrush, its influence factors can be summarized as the geological structure and mining pressure, the aquifer water properties, and the water resistance ability of floor strata; the mechanism of each influence factor is described herein. The research history and status of mine floor water inrush are introduced, and the commonly used prediction methods of mine floor water inrush grade are summarized and categorized as empirical formula methods and GIS technology, mathematical analysis methods, nonlinear mathematical analysis methods and simulation experiment methods; a detailed analysis of each method is presented. With the development of big data, cloud computing and nonlinear algorithm research, the existing deficiencies of floor water inrush prediction methods will likely be addressed by the future research and development trends of mine floor water inrush grade prediction.     

基于灰色模糊模型的塔山煤矿构造复杂程度定量评价

为实现大同煤田塔山煤矿构造复杂程度的定性-定量综合分析和分区评价,本次研究充分收集研究区钻孔实测数据和井田详查和勘探阶段的区调资料,以及各煤层采掘工程平面图,统计了研究区近百条褶皱和断裂构造产状、落差和延伸长度等参数,绘制了研究区构造纲要图.厘定了断层密度、断层强度、断层影响指数和褶皱的平面变形系数4个构造评价指标,应...