Qiu Mei, Shao Zhendong, Zhang Weiqiang, Zheng Yan, Yin Xinyu, Gai Guichao, Han Zhaodi, Zhao Jianfei
College of Earth Sciences and Engineering, Shandong University of Science and Technology, Qingdao, 266590, China.
Key Laboratory of Sedimentary Mineralization and Sedimentary Minerals in Shandong Province, Shandong University of Science and Technology, Qingdao, 266590, China.
Sci Rep. 2024 Mar 18;14(1):6465. doi: 10.1038/s41598-024-57033-x.
Clastic rock aquifer of the coal seam roof often constitutes the direct water-filling aquifer of the coal seam and its water-richness is closely related to the risk of roof water inrush. Therefore, the evaluation of the water-richness of clastic rock aquifer is the basic work of coal seam roof water disaster prevention. This article took the 4th coal seam in Huafeng mine field as an example. It combined the empirical formula method and generalized regression neural network (GRNN) to calculate the development height of water-conducting fracture zone, determined the vertical spatial range of water-richness evaluation. Depth of the sandstone floor, brittle rock ratio, lithological structure index, fault strength index, and fault intersections and endpoints density were selected as the main controlling factors. A combination weighting method based on the analytic hierarchy process (AHP), rough set theory (RS), and minimum deviation method (MD) was proposed to determine the weight of the main controlling factors. Introduced the theory of unascertained measures and confidence recognition criteria to construct an evaluation model for the water-richness of clastic rock aquifers, the study area was divided into three zones: relatively weak water-richness zones, medium water-richness zones, and relatively strong water-richness zones. By comparing with the water inrush points and the water inflow of workfaces, the evaluation model's water yield zoning was consistent with the actual situation, and the prediction effect was good. This provided a new idea for the evaluation of the water-richness of the clastic rock aquifer on the roof of the mining coal seam.
煤层顶板碎屑岩含水层常构成煤层的直接充水含水层,其富水性与顶板突水风险密切相关。因此,碎屑岩含水层富水性评价是煤层顶板水害防治的基础工作。本文以华丰井田4号煤层为例,结合经验公式法和广义回归神经网络(GRNN)计算导水裂隙带发育高度,确定富水性评价的垂向空间范围,选取砂岩底板深度、脆性岩石比例、岩性结构指数、断层强度指数以及断层交点和端点密度作为主要控制因素,提出基于层次分析法(AHP)、粗糙集理论(RS)和最小离差法(MD)的组合赋权法确定主要控制因素权重,引入未确知测度理论和置信度识别准则构建碎屑岩含水层富水性评价模型,将研究区划分为富水性相对较弱区、中等富水区和富水性相对较强区。通过与突水点及工作面涌水量对比,评价模型的涌水量分区与实际情况相符,预测效果良好,为采煤层顶板碎屑岩含水层富水性评价提供了新思路。