鱼田堡煤矿水文地质特征及深部突水模式分析

通过对鱼田堡煤矿各生产水平、开采区域、开采煤层涌水观测资料,以及水质化验、连通试验等资料的分析与研究,查明了该矿深部煤层开采的突水水源及突水通道——浅部与采空区融为一体的“地下水库”及深部K3（4#煤层）开采时在煤层顶板以上发育的采动离层裂隙带,为防治矿井深部突水提供了较为切合实际的水文地质依据。     

东胜煤田乌拉素矿区水文地质特征及充水因素研究

近年不断发生的突水事故,给煤矿安全生产带来严重威胁,研究矿区水文地质特征,分析矿井充水因素有重要现实意义。根据东胜煤田乌拉素矿区地质勘探和水文地质资料,对煤层开采导水裂隙带高度进行计算,结果表明:直罗组底部、含煤系地层的裂隙承压水含水层和上部煤层采空区内的积水,是煤层开采时矿井涌水的主要充水水源,矿井充水通道有断层裂隙带、封闭不良钻孔、采动导水裂隙带;其中导水裂隙带会将上部煤层采空区积水导通,使充水强度增大,矿坑涌水量增加。建议开采过程中要做到边探边采,探采结合,预防突水问题。     

断层破裂带附近采场采动效应的流固耦合分析

矿井底板突水是一个复杂的多物理场耦合问题,结合含断层破裂带条件下采场开采的工程背景,通过离散元流固耦合分析,研究了采场工作面推进过程中断层带的变形与受力情况以及底板支承压力、渗流矢量和渗流速度的动态发展规律和分布特征。相关模拟结果表明,采场中煤层的开采与断层破裂带之间是相互影响的,以支承压力为代表的采动应力是底板破坏形成导水裂隙带及断层“活化”突水的一个主要诱因,而断层的存在也使得工作面与断层带范围内的围岩应力更加集中,增大了底板破坏突水的危险性。采动过程中,底板破坏所形成的导水裂隙带主要集中在工作面前方及下方围岩中,这些区域渗流速度较大,是形成突水的主要通道。     

含裂隙煤层底板突水规律的数值模拟与工程应用

本文结合淮北杨庄矿某工作面实际工程情况, 利用NCAP-2D-W对煤层底板突水进行多方案的数值模拟试验研究。主要内容包括:(1) 考虑在承压水不变的条件下,设计不同裂隙分布状态,探讨单裂隙、多裂隙、不同长度裂隙对煤层底板破坏的影响及开采矿压对裂隙顶部破坏的影响;(2) 考虑承压水的变化,分别考虑单裂隙和多裂隙两种分布状态,探讨裂隙对煤层底板破坏的影响及开采矿压对裂隙底部破坏的影响。通过分析受采动荷载、岩层结构变化、煤层底板中裂隙分布状态及承压水变化等因素影响的数值试验,获得了随开采工作面不断推进煤层底板破坏区的发展、突水导升高度的递增、突水通道的形成等相关规律。     

永城矿区煤层底板裂隙灰岩突水机理

根据永城矿区的水文地质条件以及煤层底板裂隙突水的情况,划分出开放裂隙突水、闭合引张裂隙突水、递进导升突水等3种类型,并分析了各种类型突水的特征和突水机理。      

深埋土岩接触带下导水裂隙带发育规律

为了探寻深埋土岩界面下压架突水事故的机理,在分析高水压裂隙岩体赋存特征的基础上,基于导水裂隙带高度实测值及钻孔简易水文观测资料,采用理论及主控因素影响分析研究了深埋砂土砂岩界面下导水裂隙带的发育规律,研究结果表明:近深埋土岩界面带煤层开采,裂采比与防水煤岩柱高度符合Boxlucas1指数函数模型;当煤层顶板岩层大部分位于风化带深度范围时,风化带岩性的存在对导水裂隙带的高度发育起到了一定的抑制作用;风化带厚度对导水裂隙带的高度起到一定的抑制作用;而砂土砂岩界面下,由于下渗带的存在,水对岩体强度的影响,使得处于下渗带内岩层实际对导水裂隙带高度抑制作用相应的增大。     

矿山压力对底板破坏深度监测研究

目前肥城煤田6 1%的煤炭储量受底板奥陶系灰岩岩溶水威胁,采场底板破坏深度的监测是该煤田底板水害防治的重要内容,选择肥城煤田曹庄井田8煤层和9煤层开采作为监测对象,利用向底板岩层注水方法监测岩层破坏情况。利用专利产品“钻孔双端封堵测漏监测仪”,监测煤层采前的底板原始裂隙发育程度和采后矿山压力底板的破坏深度。监测结果表明,8煤层开采造成的底板破坏深度可达36.5m;9煤层开采底板破坏深度可达14.2m。      

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。     

基于板壳和断裂力学理论的上覆采空区积水危险性判定技术

为避免山西临汾胜利煤矿10号煤层采动过程中受上覆6号煤层采空区透水的威胁,利用板壳理论、断裂力学理论分别建立导水裂隙带高度和底板破裂深度的力学模型,计算10号煤层Ⅰ—Ⅵ区开采过程中导水裂隙带高度分别为46.77 m、48.86 m、56.05 m、56.14 m、56.33 m和55.20 m,6号煤层Ⅰ—Ⅳ区的破裂带影响深度分别为1.57 m、1.14 m、1.85 m和1.26 m。通过构建上覆煤层采空区积水危险性类型的划分准则,对10号煤层采动过程中受到上覆6号煤层采空区积水的危险性进行判定分析,结果表明:6号煤层Ⅰ—Ⅳ区对10号煤层的积水危险性类型均为突水型,会对10号煤开采过程产生安全威胁;6号煤层的不可采区域对10号煤层Ⅴ区和Ⅵ区的影响类型为原岩渗透型,对10号煤层Ⅴ区和Ⅵ区的回采不会构成危险性。      

底板导水裂隙带中含承压水裂隙的力学特性

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。     

大采深工作面煤层底板采动破坏深度测试

针对邢东矿大采深的情况,利用现场底板注水试验对2121工作面底板采动破坏深度进行了测试研究,依据单位注水量的动态变化以及注水孔与采线之间的距离关系,确定了底板破坏深度。试验结果表明:该工作面底板破坏深度为32.5~35m,比300m采深以内的工作面实测深度(9.15~12.0m)增加2倍以上,说明随着开采深度的增加,煤层底板采动破坏深度呈明显增大的趋势,因此,在水压和破坏深度二者同时增加的条件下,2121工作面深部煤层开采的突水危险性远远大于浅部煤层。测试结果为邢东矿大采深工作面的防治水方案的制订提供了科学依据。      

关于突水系数的讨论

煤层底板突水在我国华北型煤田矿井采煤过程中经常发生。带压开采条件下,预测底板突水和评价突水危险程度的主要方法是突水系数法,但是关于突水系数计算、临界突水系数的确定等还存在一些值得讨论和研究的问题。在阐述带压开采和突水系数理论的基础上,给出了突水系数的各种计算公式及公式中有关参数确定方法,详细说明了临界突水系数的由来和应用条件,提出了计算突水系数的新公式。新公式不仅考虑了水压和隔水层厚度,而且考虑了底板破坏深度、导升高度和奥灰顶部隔水段等因素,为计算和统计分析确定突水系数新的临界值奠定了基础。      

范各庄矿12煤底板突水过程模拟分析

以范各庄煤矿水文地质条件为基础,建立了承压水上采煤的岩体水力学模型,应用岩石破裂过程渗流-应力耦合分析系统(RFPA2D-Flow)模拟分析了范各庄矿12煤层底板开采扰动下,裂隙形成、扩展到突水通道最终贯通形成突水的全过程。通过对损伤区分布、应力场和渗流场的演化分析,揭示了开采扰动及水压驱动下完整泥岩底板由隔水岩层到突水通道的演化过程,对突水通道进行了模拟定位,并对不同水压条件下含水砂岩层对底板突水的影响进行了分析。结果表明:12煤底板突水问题取决于含水砂岩中的水压力,在假设隔水层厚度不变时,水压力与突水系数呈正相关关系,随着水压的增大突水越易发生。该研究为12煤底板突水预测与防治提供了理论依据。      

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.     

Application of a BP neural network in predicting destroyed floor depth caused by underground pressure

Predicting the destroyed floor depth caused by the mining of coal seams is of great importance in judging whether the mining of a deep coal seam can be safely performed above a confined aquifer and to prevent the inrush of water from the floor. Thirty sets of coal mining data on destroyed floor depth were selected for study. A comprehensive analysis of the factors that influence the depth of destruction of coal seam floor strata was performed and combined with the ability of a BP neural network to address dynamic nonlinear information. Then, a set of test samples was assembled and used to construct a predictive model using a BP neural network. The model was then used to predict the destroyed floor depth of the 7105 working face of the Baizhuang Coal Mine in the Feicheng coal field. To verify the effectiveness of the model, the depth of the destroyed strata comprising the coal seam floor was measured using equipment called the “Double Sided Sealed Borehole Water Injection Device.” By comparing the predictions made by the BP neural network with actual measurements, the conclusion was reached that a BP neural network model can effectively be used to predict the destroyed floor depth caused by the mining of a coal seam.     

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.     

彬长矿区复合煤层联合开采区涌水特征

针对陕西彬长矿区复合煤层联合开采工作面的涌水异常,通过总结涌水特征,找出了涌水与地层、地质构造、地层压力等之间的联系,并从涌水水源、导水通道、涌水机理3个方面分析了涌水异常的原因。分析认为,受开采强度和安定组地层因素影响,洛河组已成为煤层开采的直接或间接充水含水层;褶曲构造产生的大倾角地层利于导水裂隙带发育,是形成密集出水区段条带特征的直接原因;区域地层具备产生离层水的条件,而特殊的煤层组合关系及开采顺序是造成工作面涌水峰值巨大的主要原因。      

Study of a roof water inrush prediction model in shallow seam mining based on an analytic hierarchy process using a grey relational analysis method

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.     

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。