侯恩科, 龙天文, 刘庆利, 王飞, 樊志刚. 基于ArcGIS的洛河组含水层富水性评价[J]. 煤田地质与勘探, 2019, 47(2): 151-156. DOI: 10.3969/j.issn.1001-1986.2019.02.023
引用本文: 侯恩科, 龙天文, 刘庆利, 王飞, 樊志刚. 基于ArcGIS的洛河组含水层富水性评价[J]. 煤田地质与勘探, 2019, 47(2): 151-156. DOI: 10.3969/j.issn.1001-1986.2019.02.023
HOU Enke, LONG Tianwen, LIU Qingli, WANG Fei, FAN Zhigang. Analysis of water abundance characteristics of sandstone aquifer in Luohe Formation on the basis of ArcGIS[J]. COAL GEOLOGY & EXPLORATION, 2019, 47(2): 151-156. DOI: 10.3969/j.issn.1001-1986.2019.02.023
Citation: HOU Enke, LONG Tianwen, LIU Qingli, WANG Fei, FAN Zhigang. Analysis of water abundance characteristics of sandstone aquifer in Luohe Formation on the basis of ArcGIS[J]. COAL GEOLOGY & EXPLORATION, 2019, 47(2): 151-156. DOI: 10.3969/j.issn.1001-1986.2019.02.023

基于ArcGIS的洛河组含水层富水性评价

Analysis of water abundance characteristics of sandstone aquifer in Luohe Formation on the basis of ArcGIS

  • 摘要: 含水层富水性评价是矿井涌水量预测与水害防治的重要基础。选取彬长文家坡煤矿41盘区4号煤层顶板白垩系洛河组含水层的厚度、孔隙度、含水率、上段视电阻率、下段视电阻率和冲洗液消耗量6个主控因素,利用层次分析法(AHP)确定各主控因素的权重。在ArcGIS数值可视化软件上对各影响因素的矢量图进行归一化处理和叠加分析,构建了基于多因素融合的含水层富水性评价模型,并对41盘区富水性进行了分区评价。利用钻孔单位涌水量和4101工作面涌水量变化数据对洛河组富水性评价结果进行了验证分析,结果表明该模型的分区评价结果与实际符合,为彬长矿区洛河组含水层富水性评价提供了重要依据。

     

    Abstract: Aquifer water abundance evaluation is the prerequisite for coalmine water inflow prediction and water disaster prevention. Luohe aquifer is the roof of No.4 coal seam on panel 41 in Wenjiapo mine. Six main controlling factors of Luohe aquifer chosen to assess coal water abundance are aquifer thickness, porosity, moisture content, washing liquid consumption and apparent resistivity of upper and lower Luohe Formation. Analytic hierarchy process(AHP) has been used to determine the weight of each control factor. Based on ArcGIS numerical visualization platform, the vector maps of factors are normalized and superimposed, and then water abundance evaluation model of aquifer based on multifactor has been built and applied in panel 41. Comparing the prediction results to unit discharge of water in the borehole and discharge data, it shows that the prediction results by model application match the field data. The model could provide a powerful basis to water abundance assessment of Luohe Formation aquifer in Binchang coalfield.

     

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