基于拟线性Zoeppritz方程叠前反演的煤层顶板岩性及坚硬程度预测

    Prediction of lithology and hardness of coal seam roof based on pre-stack inversion of quasi-linear Zoeppritz equation

    • 摘要: 煤层顶板岩性及坚硬程度直接关乎巷道的稳定性和透水性,并且会直接影响煤矿的安全生产。目前,AVO反演预测地层岩性及物性已成为常见手段,但常规AVO反演公式均是在一定条件下对精确Zoeppritz方程的不同程度简化近似,在一定程度上影响反演精度。在顶板岩石物理分析基础上,将全角度误差最小的拟线性Zoeppritz方程叠前反演应用于山西阳泉矿区煤层顶板岩性及坚硬程度的预测,结果表明:拟线性Zoeppritz方程表达式简单,且通过对不同的Zoeppritz近似公式进行AVO特征分析,发现拟线性Zoeppritz方程的精度最高,仅次于精确Zoeppritz方程。岩石力学特征分析表明:杨氏模量与密度的乘积对顶板坚硬程度最为敏感,拟伽马纵波速度能有效反映顶板岩性,将反演得到的岩性及坚硬程度表征参数结合钻孔数据及地质数据综合评价顶板稳定性,为巷道掘进提供地质依据并降低煤矿生产风险。

       

      Abstract: The lithology and hardness of the coal seam roof are directly related to the stability and water permeability of the roadway and the safe production of the coal mine. It has become a common method to predict gas content based on AVO inversion, but the conventional AVO inversion formula is a simplified approximation of Zoeppritz equation in different degrees under certain conditions, which affects the inversion accuracy to some extent. On the basis of petrophysical analysis of the roof, the pre-stack inversion of quasi-linear Zoeppritz equation with the smallest overall angle error was employed to lithology and hardness prediction of coal seam roof in Yangquan Mining Area, Shanxi Province. The results show that the expression of quasi-linear Zoeppritz equation is simple, and through the AVO characteristic analysis of different Zoeppritz approximate formulas, found that the precision of quasi-linear Zoeppritz equation is the highest, second only to that of accurate Zoeppritz equation. The analysis of rock mechanics characteristics shows that Young’s modulus multiplied by density is the most sensitive to hardness, and pseudo-gamma P-wave velocity can effectively reflect roof lithology. The lithology and hardness characterization parameters obtained from inversion are combined with the parameter well data and geological data to comprehensively evaluate the roof stability, provide geological evidence for roadway excavation and reduce the coal mine production risk.

       

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