同位素在判断地下水来源方向中的应用研究

焦家金矿多年水质资料显示:随着开采深度增加,矿坑水TDS值呈现增加趋势,矿山巷道内部分涌水点水质指标成倍于浅部含水层,个别突水点涌水量多年稳定在80 m3/h左右,TDS值达到或超过14. 8 g/L。高矿化度水的来源在以往矿产勘查报告中解释为古岩相封存水,报告结论是“矿坑水与海水没有明显水力联系”。但是,矿山开采几十年,高矿化度突水点也被揭露十多年了,古岩相封存水经过长期释放应该水压降低,流量减少,基岩含水层(蚀变花岗岩或变辉长岩内的裂隙)地下水静储量也不会太多,除非有稳定水头,才能维持突水点流量稳定。难道海水成为它们的补给源?不经过深入研究,仅凭“水咸”和矿化度高这些“证据”,无法得出矿坑水与海水有水力联系的结论。近几年,Cl-同位素在水文地质学的应用为解决疑问提供了较好的思路与方法。利用37Cl作为海水侵入示踪剂,确认海水与矿坑水是否存在水力联系以及联系程度,正确认识矿坑充水因素,将焦家金矿床矿坑充水因素矢量化,对矿床深部勘查过程中矿坑涌水量预测具有指导意义。     

用灰色关联度分析法判别矿井突水水源

某湖下开采的煤矿发生突水,应用灰色关联度分析法,把突水时矿坑水的水质资料作参考序列,把湖水和煤层上覆砂岩含水层的水质资料作比较序列,对各序列作标准化处理,计算出关联系数,进而求出关联度,比较影响因素(湖水和砂岩水)对研究对象(矿坑水)的贴近程度,得出结论:矿井突水水源为砂岩水,与湖水无关。      

水文地质工作在矿业整装勘查中的重要作用与现实意义

矿坑(井)涌(突)水造成重大安全事故事件频繁发生,并因矿坑巨量涌水淹没矿井而抽排水造成开矿成本增高。因此,进行水文地质研究,降低矿坑(井)涌(突)水给矿井建设和生产带来的危害,实现矿山安全生产,对于矿业工作来说,有着重要作用和现实意义。     

甘肃省矿山地质灾害及其基本特征

甘肃是矿产资源大省,矿产开发利用规模大、强度高,因而矿山地质环境问题突出,其中矿山地质灾害的危害和威胁尤其严重。本文基于实际调查数据,论述分析了甘肃省矿山地质灾害的主要类型、基本特征及其危害特点。根据调查结果,甘肃省主要发育五类矿山地质灾害:采空地面塌陷、滑坡、崩塌、泥石流和矿坑突水。在这五类灾害中,采空地面塌陷分布最广、造成的直接经济损失最严重,滑坡发生频次高、造成人员伤亡最大,矿坑突水灾害分布范围、发生频次和危害程度相对最低。各类灾害的分布和发育特征受地质环境条件及矿山开采规模和开采方式的控制,灾害的危害特点与其分布和发育特征和活动特点有关。     

攀枝花宝鼎煤矿矿井充水因素分析

根据矿区水文地质条件,用以往矿井“突水”实例、现象、充水来源、充水条件,对矿坑充水因素进行分析,以预防矿井因充水而产生的淹井和人员伤亡事故。     

最优分割法在采煤工作面突水量预报中的应用

矿坑突水量预报是一个在理论和实践上尚未解决的问题，本文首次将最优分割应用于突水水量预报问题中，确定出适合于采煤工作面突水量的预报方案。最优分割法是以因子的取顺序对预报量进行最优二分割的，如果因子与预报量之间呈正相关、负相关或某种趋势联系，这些规律往往在因子分段之后才能反映出来，这正是其它预报方法无法比拟的。     

用灰色关联度分析半判别矿井突水水源

某湖下开采的煤矿发生突水，应用灰色关联度分析法，把突水时矿坑水的水质资料作参考序列，把湖水和煤层上覆砂岩含水层的水质资料作比较序列，对各序列作标准化处理，计算出关联系数，进而求出关联度，比较影响因素（湖水和砂岩水）对研究对象（矿坑水）的贴近程度，得出结论：矿井突水水源为砂岩水，与湖水无关。     

“溶洞泥”等固体物突入矿坑问题

<正> 笔者在进行矿坑突水研究过程中,注意到给矿坑带来危害的除突水外,还存在着固体物质突入(简称突固)问题。由于‘突固’,常常给矿坑造成极为严重的恶果。固体物的物源、突出原因、影响突出的因素及其防治方法同样与岩溶工程地质水文地质条件密切相关。岩溶类型和部份其它类型的煤矿,已出现的突固现象有“岩爆”突出煤、岩石块;“溃砂”;突砂石流;溶洞突泥等。前者采矿界有的称之为“岩爆”、“矿山弹射”,突砂石流又称之为“流砂溃入”。溶洞突泥现象是近年来发现的问题。固体物突出的物源、储积条件、突出机理是不相同的。现就看到和收集到的突固工程地质、水文地质现象进行初步探讨以引起同行们对此问题的关注,有益于采矿事业。      

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。      

淄博市矿坑水利用现状分析

调查研究了目前矿坑水利用途径,适用于淄博市矿坑水的处理方法。调查了全市各类矿山矿坑水排水总量和现状利用量。在现状利用的基础上,经分析淄博市矿坑水可利用潜力为1392万m3。根据矿坑水可利用量和各行业的实际需水情况,制定了各区县详细的再生水利用规划方案。     

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.     

矿井突水水源判别的多组逐步Bayes判别方法研究

矿井突水是采矿过程中最具威胁的自然灾害之一。能否准确快速地判别矿井突水水源,不仅是矿井水文地质工作的主要内容,而且是煤矿防治水工作的重要基础。为了有效判别矿井突水水源,综合考虑水化学指标对水源判别的重要性,基于多组逐步Bayes判别分析理论,选取Na+ K+、Ca2+、Mg2+、Cl-、SO42-和HCO3-共6项指标作为判别因子,利用国内某矿区各主要含水层的35个水样的水质资料作为训练样本,建立了矿井突水水源预测的多组逐步Bayes判别分析模型。实例分析表明,该模型结果与实际情况相符合,说明该模型在矿井突水水源判别中具有良好的实用性和有效性,为判别矿区新的突水水源提供了一种新思路。     

Evaluation on Water Burst (inrush) Risks on 15# Coal Seam Roof of Shigejie Coal Mine of Shaanxi Lu’an Group

Based on the analysis of the hydrogeological conditions and water burst (inrush) conditions on 15# coal seam roof of Shigejie coal mine of Shanxi Lu’an Group, this article evaluated the water burst (inrush) risks on 15# coal seam roof of Shigejie coal mine with the multi-source information composite technology and marked out the zones with medium and small water burst (inrush) risks on 15# coal seam roof of Shigejie coal mine. The targeted water prevention and control measures were proposed in accordance with the results of research evaluation     

邢台煤矿下组煤开采水文地质条件评价及突水危险性预测

为安全开采下组煤,详细分析了矿区奥灰水文地质条件,以研究煤层底板突水因素、突不机理为切入点,利用地理信息系统技术,对下组煤开采之前奥灰突水的危险性进行了预测,即可分为３个区（安全区、可能突水区、突水区）,同时提出下组煤先期开采的范围为－２１０ｍ水平以上范围。     

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.     

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。      

多源数据挖掘下潘谢矿区深部灰岩水突水预警研究

深层灰岩水在长时间水岩耦合作用下各含水层的水化学成分有所不同,但随着地壳运动、采动影响等因素导致不同含水层产生水力联系。重大的突水事故都是深层高压灰岩水以浅层灰岩水为通道突入矿井发生的。依据对淮南煤田潘谢矿区9对矿井2015—2018年182个地面水文观测孔的水位数据及潘二矿突水后各水文观测孔水位变化的时空规律,得出水文观测孔的水位变化数据比水位高程数据更灵敏,潘谢矿区深层灰岩水由下向上对浅层灰岩水进行补给,通过聚类分析算法识别出矿井与深层灰岩水存在补给关系的浅层灰岩含水层区域;另一方面基于改进的随机森林算法对收集的7 000多条矿井水质化验资料进行分析,基于错分数据识别出与深层灰岩水水力联系紧密的各矿含水层信息。综合分析水位变化数据聚类分析结果,得出各矿井的突水风险区域。基于含水层分类显著因子、水化学空间分布特征,结合温度、流量、水位、水质等参数的高精度传感器,构建快速准确突水预警系统,对矿井出水点进行智能监测,为实施防治水措施提供快速、可靠的依据,可以极大地避免矿井发生突水事故和减少突水事故产生的损失。      

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.