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    TI介质像域非迭代最小二乘高斯束偏移

    Non-iterative least-squares Gaussian beam migration in image domain for TI media

    • 摘要: 高斯束偏移具有高效、灵活的优势,且对各向异性介质有良好的适应性,在地震成像中得到了广泛应用。基于高斯束的最小二乘偏移理论上具有良好的成像精度,但其在计算效率和稳定性方面仍面临诸多挑战。为提升地下复杂构造的成像质量,提出一种基于横向各向同性(TI)介质的像域非迭代最小二乘高斯束偏移方法。首先,利用TI射线追踪计算高斯束的旅行时与振幅,构建TI介质下的格林函数;然后,基于该格林函数解析可表征地下空间的点扩散函数,并将其作为Hessian矩阵的近似。最后,利用点扩散函数对经典TI高斯束偏移结果进行高维反褶积处理,实现TI介质中的像域非迭代最小二乘偏移成像。合成模型数值测试结果表明,该方法在TI介质中具有良好的成像效果,实际地震数据的应用结果进一步证明了其应用潜力。

       

      Abstract: The Gaussian beam migration method is widely used in seismic imaging due to its high efficiency, flexibility, and good adaptability to anisotropic media. Least-squares migration (LSGBM) based on Gaussian beams theoretically offers superior imaging accuracy, yet it still faces challenges in computational efficiency and stability. To improve the imaging quality of subsurface complex structures, this paper proposed an image-domain non-iterative least-squares Gaussian beam migration method suitable for transversely isotropic (TI) media. First, anisotropic ray tracing was employed to compute the travel time and amplitudes of Gaussian beams, thereby constructing the Green’s functions for TI media. Subsequently, the point spread function (PSF) of the subsurface space was analytically characterized based on the Green’s function, serving as an approximation of the Hessian matrix. Finally, the point spread function was used to perform high-dimensional deconvolution on the classical anisotropic Gaussian beam migration result, achieving image-domain non-iterative least-squares migration imaging in TI media. Validation using synthetic models demonstrates the method’s good imaging performance in TI media, and application to real seismic data further confirms its potential.

       

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