基于多地质因素的多属性地质建模方法研究

Multi-attribute geological modeling method based on multiple geological factors

  • 摘要:
    目的 为解决煤层底板突水隐蔽致灾因素辨识难度大的问题,提升煤矿水害防治水平,提出一种基于多地质因素的多属性地质建模方法。
    方法 系统分析煤层底板突水的静态原生隐蔽导水地质因素和动态采动隐蔽导水地质因素的特征及耦合致灾机制;梳理采煤工作面物探、钻探、采掘揭露三类地质探查数据并分析其数据特征与应用价值;提出 DE-Kriging 耦合插值算法构建高精度基础几何地质模型,进一步融合多类地质因素构建可表征静动态信息的多属性地质模型。
    结果 以鄂尔多斯某煤矿61304工作面为应用实例,基于随采地震等监测数据构建多属性地质模型,识别出工作面前方SYC1、SYC2两处潜在导水异常区,明确了异常区的空间分布范围及对底板的影响深度,预判其存在底板突水风险。
    结论 所构建的多属性地质模型可有效集成各类隐蔽致灾因素信息,为采前煤层底板突水脆弱性指数计算和采中有效隔水层厚度计算提供关键支撑,对矿井水害防治具有重要指导意义。

     

    Abstract: To address the difficulty in identifying concealed hazards contributing to water inrush from coal seam floor, and to enhance the level of water hazard prevention and control in coal mines, this paper proposes a multi-attribute geological modeling method based on multiple geological factors. Firstly, the characteristics and coupled disaster-causing mechanisms of static primary concealed water-conducting geological factors and dynamic mining-induced concealed water-conducting geological factors in coal seam floor water inrush are analyzed. Secondly, three types of geological exploration data, including geophysical exploration, drilling exploration, and mining and excavation exposure, are sorted out and their data characteristics and application values are analyzed. Finally, the DE-Kriging coupled interpolation algorithm is proposed to construct a high-precision basic geometric geological model, and further integrate multiple geological factors to build a multi-attribute geological model that can represent static and dynamic information. Taking the 61304 working face of a coal mine in Erdos as an application example, a multi-attribute geological model was constructed based on monitoring data such as seismic data during mining. Two potential water-conducting anomaly zones, SYC1 and SYC2, were identified ahead of the working face. The spatial distribution range of the anomaly zones and their impact depth on the floor were clarified, and the risk of water inrush from the floor was predicted. The constructed multi-attribute geological model can effectively integrate various concealed hazard-causing factors, providing crucial support for calculating the vulnerability index of water inrush from coal seam floor before mining and the effective thickness of water-resisting layer during mining.

     

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