Study on Numerical Simulation of Overburden Fracture Development Characteristics and Prediction of Water-Conducting Fracture Zone Height in Shallow Coal Seam Mining

IF 1.2 4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Geofluids Pub Date : 2025-03-19 DOI:10.1155/gfl/8283522
Qingbiao Guo, Yang Cai, Boqing Qiao, Yongqiang Zhao, Yingming Yang, Xuejia Li
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Abstract

The northern Shanxi mining region, a pivotal coal-rich area in China, is characterized by substantial reserves of shallow coal seams and distinctive geological mining conditions that exacerbate overburden rock fissure development. This study delves into the mechanisms governing overburden damage and fissure evolution in shallow coal seams using the theoretical frameworks of key strata and mining subsidence, augmented by numerical simulation methodologies. It also examines the impact on ground fissure morphology and propagation. Additionally, this paper investigates the prediction of water-conducting fracture zone heights in shallow coal seams. This paper’s findings reveal a sequential dynamic process in overburden rocks during mining: microfissure initiation, key stratum rupture, fissure aggregation, and fissure coalescence. Leveraging a long short-term memory (LSTM) model, this paper develops a prediction model for water-conducting fracture zone heights in shallow coal seams, achieving high accuracy with a mean squared error (MSE) of 2.29, a mean absolute error (MAE) of 1.22, and an average relative error of 2.51%. These results contribute scientific insights for mitigating ground fissure disasters and facilitating ecological restoration in the context of intensive shallow coal seam mining in northern Shanxi. Furthermore, they hold substantial scientific merit in advancing the theories of mining subsidence and stratum control in mining engineering.

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浅埋煤层覆岩裂隙发育特征数值模拟及导水裂隙带高度预测研究
陕北矿区是中国重要的煤炭富集区,其浅层煤层储量丰富,地质开采条件独特,上覆岩裂隙发育加剧。本研究利用关键层和开采沉陷的理论框架,结合数值模拟方法,深入研究了浅层煤层覆盖层损伤和裂隙演化的机理。它还研究了对地裂缝形态和扩展的影响。此外,本文还对浅埋煤层导水裂隙带高度的预测进行了研究。研究结果揭示了采动过程中覆岩微裂隙萌生-关键层破裂-裂隙聚集-裂隙合并的顺序动力学过程。利用长短期记忆(LSTM)模型,建立了浅层煤层导水裂隙带高度预测模型,预测精度较高,均方误差(MSE)为2.29,平均绝对误差(MAE)为1.22,平均相对误差为2.51%。研究结果为在晋北浅埋煤层密集开采背景下减轻地裂缝灾害、促进生态恢复提供了科学依据。在推进采矿沉陷理论和采矿工程地层控制方面具有重要的科学价值。
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来源期刊
Geofluids
Geofluids 地学-地球化学与地球物理
CiteScore
2.80
自引率
17.60%
发文量
835
期刊介绍: Geofluids is a peer-reviewed, Open Access journal that provides a forum for original research and reviews relating to the role of fluids in mineralogical, chemical, and structural evolution of the Earth’s crust. Its explicit aim is to disseminate ideas across the range of sub-disciplines in which Geofluids research is carried out. To this end, authors are encouraged to stress the transdisciplinary relevance and international ramifications of their research. Authors are also encouraged to make their work as accessible as possible to readers from other sub-disciplines. Geofluids emphasizes chemical, microbial, and physical aspects of subsurface fluids throughout the Earth’s crust. Geofluids spans studies of groundwater, terrestrial or submarine geothermal fluids, basinal brines, petroleum, metamorphic waters or magmatic fluids.
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