基于KTM−剖平投影法的煤矿透明工作面建模技术

    Modeling technology of transparent working face in coal mine based on KTM-flattening projection method

    • 摘要: 为提高煤矿透明工作面三维地质模型精度,满足煤炭安全、高效、智能开采需求,采用KTM(Kriging-Triangulation Mesh)−剖平投影法构建高精度三维地质模型,并进行实例应用。利用孔斜校正和剖平投影技术对钻孔、工作面剖面图等原始数据进行二次处理,采集目标工作面边界周边更多煤层和构造控制数据,增加已知点数据源数量;结合地质构造资料对断层轨迹线进行边界、属性设置,通过KTM−剖平投影法对点数据进行加密、均匀排列和平滑处理,结合不规则三角网和似直三棱柱模型完成高精度工作面地质模型的构建。应用该方法构建了山西省保德县某矿区12105工作面地质模型,并提取所建模型剖面图中煤层底板点数据与现场实测地质数据进行对比分析。经验证,模型误差值均在0.2 m以内,其中误差范围在0~0.1 m的点数据占整体90%,满足复杂地质条件下三维模型精度要求。结果表明:采用该建模方法可以有效提高地质模型中空间点数据的精确度与密集度,使得所建模型更为精细,可以更加完整、准确地表达地质体目标区域的地质特征。同时,构建了该矿区12105工作面顶板、底板和回采巷道模型,为实现煤矿智能开采提供了重要数据支持。

       

      Abstract: In order to improve the accuracy of 3D geological model of transparent working face in coal mine and meet the needs of coal safety, high efficiency and intelligent mining, we proposed to construct a high-precision 3D geological model by using Kriging-triangulation mesh (KTM) -flattening projection method and applied it to an example. Collect more coal seam and structural control data around the boundary of the target working face to increase the number of known point data sources. Set the boundaries and attributes of fault trajectory lines in combination with geological structure data. Densify, uniformly arrange and smooth the point data through the KTM-flattening projection method. Complete the construction of a high-precision working face geological model by integrating the triangulated irregular network (TIN) and the quasi-rectangular triangular prism model. The method was applied to construct the geological model of the 12105 working face in a mining area of Baode County, Shanxi Province. The coal seam floor point data extracted from the cross-sections of the built model were compared and analyzed with the on-site measured geological data. Verification results show that all model error values are within 0.2 m, among which the point data with errors ranging from 0 to 0.1 m account for 90% of the total, meeting the accuracy requirements of 3D models under complex geological conditions. The results show that the proposed modeling method can effectively improve the accuracy and density of spatial point data in the geological model, making the constructed model more refined and enabling it to express the geological characteristics of the target area of the geological body more completely and accurately. Meanwhile, the roof, floor and mining roadway models of the 12105 working face in the mining area have been constructed, providing important data support for the realization of intelligent coal mining.

       

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