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    基于卡尔曼局地化的页岩油储层地震各向异性随机反演

    Kalman localization based seismic anisotropic stochastic inversion for shale oil reservoirs

    • 摘要: 页岩油这类非常规储层受粘土矿物及微孔隙定向排列影响具有强各向异性,导致地震响应高度复杂化。传统反演方法难以精确刻画各向异性参数,从而影响页岩油储层裂缝的精确表征与综合评价。为高效且高精度地表征页岩油储层,采用Zoeppritz方程替换Rüger近似中的各向同性项,提高大角度入射时反射系数的计算精度,增强各向异性参数对反演方程的敏感性;同时,引入卡尔曼局地化技术,有效抑制小样本集合计算产生的虚假相关性,形成从局地化尺度分析、先验地质统计学模拟到多参数迭代更新与不确定性评估的完整反演流程。模型试算与实际应用表明,该方法在小规模先验集合下可实现弹性与各向异性参数的高精度稳定反演,反演结果符合地质规律,与测井观测数据高度一致,在计算效率与抗噪性能方面具有显著优势,可为后续页岩油储层裂缝的精细刻画与甜点综合评价提供可靠的支撑。

       

      Abstract: Unconventional reservoirs represented by shale oil exhibit pronounced seismic anisotropy resulting from the preferential alignment of clay minerals and micropores, which gives rise to highly complex seismic responses. Conventional inversion methods often fail to accurately characterize anisotropy parameters, which thereby limits the precise characterization and comprehensive evaluation of fractures in shale oil reservoirs. To achieve high-efficiency and high-precision characterization of shale oil reservoirs, this study replaces the isotropic component in the Rüger approximation with the exact Zoeppritz equations. This modification improves the calculation accuracy of reflection coefficients at large incidence angles and enhances the sensitivity of anisotropy parameters to the inversion equation. In addition, a localized Kalman filter technique is introduced to effectively mitigate spurious correlations associated with limited ensemble sizes. This improvement establishes a comprehensive inversion workflow, including localization-scale analysis, prior geostatistical simulation, multi-parameter iterative updating, and uncertainty quantification. Both synthetic experiments and field-data applications demonstrate that the proposed method can achieve stable and high-accuracy inversion of elastic and anisotropic parameters, even with relatively small prior ensembles. The inversion results exhibit strong consistency with geological features and well-log observations. By effectively balancing computational efficiency and noise robustness, the proposed method provides reliable geophysical support for subsequent fine-scale fracture characterization and comprehensive sweet-spot evaluation of shale oil reservoirs.

       

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