MULTISCALE SEISMIC WAVE-FORM INVERSION
MULTISCALE SEISMIC WAVE-FORM INVERSION
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DOI：
10.1190/1.1443880
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发表时间：
1995-09-01
期刊：
影响因子：
3.3
通讯作者：
CHAVENT, G
中科院分区：
文献类型：
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作者：
BUNKS, C;SALECK, FM;CHAVENT, G
迭代反演方法在反演从复杂地球模型（例如 Marmousi 模型）获得的地震数据方面并不成功，主要困难是目标函数中存在大量局部极小值。地震反演问题中所有尺度上局部最小值的存在阻止了迭代反演方法获得对全局最小值邻域的合理程度的收敛。多重网格方法是一种通过按尺度分解问题来提高迭代反演性能的技术。在长尺度上，局部极小值较少，而剩下的极小值彼此之间的距离更远。因此，在长尺度上，迭代方法可以更接近全局最小值的邻域。我们将多重网格方法应用于 Marmousi 数据集的二次采样、低频版本。尽管没有处理源估计、源带宽和噪声的问题，但结果表明，当采用按尺度分解时，迭代反演方法的性能要好得多。此外，该方法大大减少了反演的计算负担，这对于该方法的 3-D 扩展非常重要。
Iterative inversion methods have been unsuccessful at inverting seismic data obtained from complicated earth models (e.g. the Marmousi model), the primary difficulty being the presence of numerous local minima in the objective function. The presence of local minima at all scales in the seismic inversion problem prevent iterative methods of inversion from attaining a reasonable degree of convergence to the neighborhood of the global minimum. The multigrid method is a technique that improves the performance of iterative inversion by decomposing the problem by scale. At long scales there are fewer local minima and those that remain are further apart from each other. Thus, at long scales iterative methods can get closer to the neighborhood of the global minimum. We apply the multigrid method to a subsampled, low-frequency version of the Marmousi data set. Although issues of source estimation, source bandwidth, and noise are not treated, results show that iterative inversion methods perform much better when employed with a decomposition by scale. Furthermore, the method greatly reduces the computational burden of the inversion that will be of importance for 3-D extensions to the method.