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谢治刚,孙 贵,随峰堂,等. 基于层次分析法的地面区域治理目的层位优化选择[J]. 煤炭科学技术,2023,51(3):201−211

. DOI: 10.13199/j.cnki.cst.2021-0408
引用本文:

谢治刚,孙 贵,随峰堂,等. 基于层次分析法的地面区域治理目的层位优化选择[J]. 煤炭科学技术,2023,51(3):201−211

. DOI: 10.13199/j.cnki.cst.2021-0408

XIE Zhigang,SUN Gui,SUI Fengtang,et al. Optimum selection of target strata of ground regional treatment based on analytic hierarchy process[J]. Coal Science and Technology,2023,51(3):201−211

. DOI: 10.13199/j.cnki.cst.2021-0408
Citation:

XIE Zhigang,SUN Gui,SUI Fengtang,et al. Optimum selection of target strata of ground regional treatment based on analytic hierarchy process[J]. Coal Science and Technology,2023,51(3):201−211

. DOI: 10.13199/j.cnki.cst.2021-0408

基于层次分析法的地面区域治理目的层位优化选择

Optimum selection of target strata of ground regional treatment based on analytic hierarchy process

  • 摘要: 鉴于两淮煤田太原组地层灰岩多达10~13层,地面区域治理的目的层位具有不惟一性,以潘二煤矿西四采区18413工作面为例,对目的层位的优化选择问题进行研究。突水系数要求是目的层位优化选择的前提,决定了目的层位的选择范围,以C3 6灰岩为目的层位,经计算得出其突水系数小于临界值,因此,推断C3 6~C3 12灰岩为潜在的目的层位。水动力条件、含水层水力联系、导水构造、灰岩间距、灰岩厚度、地层可注性等影响因素是目的层位优化选择的关键指标,而单因素分析确定的目的层位之间具有不相容性,难以实现目的层位的优化选择,因此,采用层次分析法进行目的层位的优化选择。以地面区域治理目的层位的优化选择为目标层,水动力条件、含水层水力联系、导水构造、灰岩间距、灰岩厚度、地层可注性为准则层,太原组C3 6、C3 7、C3 8、C3 9、C3 10、C3 11、C3 12灰岩为方案层,建立层次分析模型;构造目标层与准则层、准则层与方案层的判断矩阵,并计算准则层各指标的权重及方案层各方案的单因素分值,经检验一致性比例CR值均小于0.10,判断矩阵一致性较好,满足一致性检验;通过层次总排序计算得到各方案的总分值分别为0.177、0.169、0.170、0.214、0.103、0.114、0.053,其中C3 9灰岩总分值最大,表明地面区域治理最优目的层位为C3 9灰岩。将层次分析法应用于地面区域治理目的层位优化选择的研究,将定性问题转化为定量问题,实现了目的层位的多因素定量化优化选择,为目的层位的优化选择提供了新方法。

     

    Abstract: In view of the fact that there were as many as 10 to 13 layers of limestone in Taiyuan formation in Huainan and Huaibei Coalfield, the target strata of ground regional treatment was not unique, the 18413 working face in the west 4th mining area of Pan'er coal mine was taken as an example, the optimization of the target strata was studied. The requirement of water inrush coefficient was the prerequisite for optimum selection of target strata, which determined the selection range of target strata. With C3 6 limestone as the target strata, the water inrush coefficient is less than the critical value after calculation. Therefore, it is inferred that C3 6-C3 12 limestone is the potential target strata. Influencing factors such as hydrodynamic conditions, aquifer hydraulic connection, water-conducting geological structure, limestone spacing, limestone thickness and stratum injectability were the key indicators for optimum selection of target strata. However, the target strata determined by single factor analysis is incompatible with each other, which makes it difficult to achieve the optimal selection of the target strata. Therefore, the analytic hierarchy process was adopted for the optimal selection of the target strata. The optimum selection of target strata of ground regional treatment was taken as the objective layer, hydrodynamic conditions, hydraulic connection between aquifers, water-conducting geological structure, limestone spacing, limestone thickness and stratum injectability were taken as the criterion layer, and C3 6, C3 7, C3 8, C3 9, C3 10, C3 11, C3 12 limestone of Taiyuan formation were taken as the scheme layer, the analytic hierarchy process model was established. The judgment matrix of the target layer and the criterion layer, the criterion layer and the scheme layer were constructed, and the weight of each index of the criterion layer and the single factor score of each scheme of the scheme layer were calculated. TheCRvalues were all less than 0.10 after inspection, and judgment matrices had satisfactory consistency, meeting the consistency test. The total score of each scheme was 0.177, 0.169, 0.170, 0.214, 0.103, 0.114 and 0.053, respectively, which were calculated by the hierarchy total sort. The total score of C3 9 limestone was the largest, indicating that the optimal target stratum of ground regional treatment was C3 9 limestone. The analytic hierarchy process was applied to the study on the optimum selection of target strata of ground regional treatment, and the qualitative problem was transformed into a quantitative problem, realizing the multi-factor quantitative optimum selection of target strata, and providing a new method for optimum selection of target strata.

     

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