基于三维地质建模技术的煤矿隐蔽致灾因素透明化研究

Research on transparency of hidden disaster causing factors in coal mines based on 3D geological modeling technology

  • 摘要: 隐蔽致灾因素是制约煤矿智能开采建设的关键问题,而三维地质建模是实现隐蔽致灾因素透明化的主要技术手段。目前煤矿三维地质建模技术以几何建模为主、属性建模为辅,缺少针对隐蔽致灾因素的灾害属性建模。针对上述问题,以陕北某煤矿作为研究对象,对煤层厚度、顶底板构造起伏、积水区、浅埋煤层地形地貌等隐蔽致灾因素进行三维地质建模。首先,完成对地质资料、物探、钻探等成果的数字化工作,建立煤矿地质数据库。其次,利用DepthInsight建模软件从全矿井和工作面2个尺度开展建模工作,即以钻孔分层数据作为地层控制点,通过煤层及地表等高线、虚拟钻孔等数据联合控制地层层序,并处理初始层面模型中的穿层异常,构建地层面模型和地质体模型,再运用数字高程模型对工作面进行地表模型构建。然后,采用岩体建模构建采空区、积水区模型并标注温度、气体等信息,利用工作面回采测量数据构建回采实测模型。最后,创建截断网格模型,通过序贯高斯模拟生成含水层渗透率、富水系数模型,实现区内水文隐蔽致灾因素透明化显示。基于三维地质模型,从地层、煤层及工作面、采空区及其积水区、水文属性多角度分析隐蔽致灾因素的分布及影响。研究成果可为煤矿隐蔽致灾因素的精准治理提供靶区,助力煤矿智能开采建设。

     

    Abstract: Hidden disaster causing factor is the key issue that restricts the construction of intelligent coal mining. The 3D geological modeling is the main technical means to achieve transparency of hidden disaster causing factors. At present, the 3D geological modeling technology of coal mines mainly relies on geometric modeling and attribute modeling as a supplement, lacking disaster attribute modeling for hidden disaster causing factors. In order to solve the above problems, taking a coal mine in northern Shaanxi as the research object, the 3D geological modeling is conducted on hidden disaster causing factors such as coal seam thickness, roof and floor structural undulations, waterlogged areas, and shallow coal seam topography. Firstly, the digitization of geological data, geophysical exploration, drilling and other achievements are completed. The coal mine geological database is established. Secondly, the DepthInsight modeling software is used to carry out modeling work from two scales: the entire mine and the working face. The drilling layer data is used as the stratigraphic control point, and the stratigraphic sequence is jointly controlled through coal seam and surface contour lines, virtual drilling, and other data. The layer crossing anomalies in the initial layer model is processed. The ground level model and geological body model are constructed. The digital elevation model is used to construct the surface model of the working face. Thirdly, rock mass modeling is used to construct models of goaf and waterlogging areas, and temperature, gas and other information are annotated. The actual mining measurement data of the working face is used to construct a mining measurement model. Finally, the truncated grid model is created. The permeability and water-rich coefficient model of the aquifer is generated through sequential Gaussian simulation to achieve transparent display of hidden hydrological disaster causing factors in the area. Based on a 3D geological model, the distribution and impact of hidden disaster causing factors are analyzed from multiple perspectives such as strata, coal seams and working faces, goaf and its waterlogged areas, and hydrological attributes. The research results can provide a target area for the precise management of hidden disaster causing factors in coal mines, and assist in the construction of intelligent mining in coal mines.

     

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