首页> 外文期刊>Journal of Environmental Protection and Ecology >WATER RICH CHARACTERISTICS OF AQUIFER AND DETERMINATION OF MINE WATER QUALITY AFTER PIT CLOSURE IN NORTHERN SHAANXI MINING AREA
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WATER RICH CHARACTERISTICS OF AQUIFER AND DETERMINATION OF MINE WATER QUALITY AFTER PIT CLOSURE IN NORTHERN SHAANXI MINING AREA

机译:陕北矿区矿井含水层水中含水量及矿井水质的测定

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摘要

With the increase of mining depth and the extension of mining level, the hydrogeological conditions are more complex, the water head pressure of the floor water filled aquifer with supply conditions is more and more large, and a series of problems such as the connection of mining coal seam and thick limestone caused by regional fault seriously restrict the environmental safety. Therefore, in the actual production process, it is of great practical significance to grasp the water rich distribution law of the water filled aquifer and predict the water drainage of the coal seam floor to ensure the effective prevention and control of mine water disaster and the safe mining of coal. According to the type and characteristics of coal mine water filled aquifer, in the case of lack of hydrogeological drilling this paper establishes a set of relatively systematic evaluation index system of coal mine water filled aquifer's water yield, and applies PNN neural network theory and method to establish a new practical model conforming to the water yield law of the aquifer to study the water filled aquifer's water yield in the study area Make new comments. The results show that the coupling model based on the distribution of sedimentary (microfacies) and PNN neural network is more accurate than the traditional information fusion method. Therefore, this evaluation method is reasonable and effective in the evaluation of water yield of sandstone fracture aquifer in Zhiluo formation.
机译:随着采矿深度的增加和采矿水平的延伸,水文地质条件更复杂,地板水的水头压力供应条件越来越大,以及一系列问题,如采矿的连接等问题区域故障引起的煤层和厚石灰岩严重限制了环境安全。因此,在实际生产过程中,掌握水含量富含含水层的水分分配规律并预测煤层船舶的排水,以确保矿井水灾和安全的有效防治煤炭采矿。根据煤矿水填充含水层的类型和特点,在缺乏水文地上钻探的情况下,本文建立了一套相对系统的煤矿水中含水量水产产量的评价指标体系,并适用于PNN神经网络理论和方法建立一个符合水含水量法的新实际模型,以研究水中含水层的水资源产量,在研究区域进行新评论。结果表明,基于沉积(微腐蚀)和PNN神经网络分布的耦合模型比传统信息融合方法更准确。因此,该评价方法是合理且有效的Zhiluo形成的砂岩骨折含水层的水产量。

著录项

  • 来源
    《Journal of Environmental Protection and Ecology》 |2020年第5期|1794-1805|共12页
  • 作者

    Dong Ying; Wu Xijun;

  • 作者单位

    Yulin Univ Sch Civil Engn Yulin 719000 Shaanxi Peoples R China|Yulin Univ Shaanxi Key Lab Ecol Restorat Shanbei Min Area Yulin 719000 Shaanxi Peoples R China;

    Yulin Univ Sch Civil Engn Yulin 719000 Shaanxi Peoples R China|Xian Univ Technol State Key Lab Ecohydraul Northwest Arid Reg Xian 710048 Shaanxi Peoples R China|Yulin Univ Shaanxi Key Lab Ecol Restorat Shanbei Min Area Yulin 719000 Shaanxi Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    water rich; sedimentary environment; aquifer; floor limestone; PNN neural network model;

    机译:富含水;沉积环境;含水层;地板石灰石;PNN神经网络模型;

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