The coherence attribute has been widely used to detect faults and channels as well as other structural and stratigraphic discontinuities since its introduction. Currently, the most commonly used algorithm for coherence computation is the eigenstructure-based coherence method (C3). When seismic data are of a low signal-to-noise ratio, more traces should be involved in coherence computation to improve the robustness to noise; thus, a larger analysis window shall be used. However, this will lead to increased time costs and blurred coherence images. To address these issues, we have adopted a modified eigenstructure-based coherency algorithm (C3m) based on an inverse distance weighting method and dimensionality reduction of the covariance matrix for eigendecomposition in the case of a large lateral analysis window whose size is larger than $3\times 3$ (nine traces). To further improve the computational efficiency, the add-drop algorithm is also used for covariance matrix construction. In the case of large analysis windows, the time cost by C3m is less than the time cost by C3 as demonstrated in synthetic and field data studies; also, the coherence results computed via C3m are superior to those computed via the traditional C3 method, and the new method is more favorable to seismic interpretation. Thus, our method shall be a potentially efficient and robust alternative to C3 for coherence attribute computation.

中文翻译：

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一种高效，鲁棒的方案，用于实现基于特征结构的相干算法

自引入以来，相干属性已被广泛用于检测断层和通道以及其他结构和地层不连续性。当前，用于相干计算的最常用算法是基于本征结构的相干方法（C3）。当地震数据的信噪比较低时，相干计算中应涉及更多迹线，以提高抗噪声能力。因此，应使用更大的分析窗口。但是，这将导致时间成本增加和相干图像模糊。为了解决这些问题，我们采用了一种改进的基于本征结构的相干算法（C3m），该算法基于逆距离加权方法，并且在横向分析窗口的大小大于10％的情况下，对本征分解的协方差矩阵进行降维处理。$3\times 3$（九条痕迹）。为了进一步提高计算效率，将拖放算法也用于协方差矩阵构造。在较大的分析窗口中，C3m的时间成本小于C3m的时间成本，如综合数据和现场数据研究所示；而且，通过C3m计算得到的相干性结果要优于通过传统C3方法计算出的相干性，而新方法更有利于地震解释。因此，对于相干属性计算，我们的方法将是C3的潜在有效且健壮的替代方法。