Obtaining accurate velocity models plays a crucial role in many routine seismic imaging algorithms. Seismic velocity models are normally made through seismic velocity analysis workflows. The routine workflows are not capable of dealing with polarity variations across moveout curves. We address this limitation by proposing a straight-forward and robust semblance-based workflow, which is a modified version of the conventional semblance function. The coherency function applies semblance analysis on separate clusters of receivers followed by averaging the corresponding coherency measures from all the clusters. The proposed approach is suitable for any case of amplitude variations including attenuation and any class of amplitude-versus-offset effects. The ability of the proposed workflow is demonstrated to two synthetic data as well as two field-recorded common-midpoint gathers. We perform accuracy analysis by comparing the results from the proposed approach with the results achieved from conventional velocity analysis, and another semblance-based algorithm that is developed to address the polarity variation task. We also studied noise sensitivity analysis by computing and comparing mathematical expectations between theory and practice.

中文翻译：

---

使用局部相似性在存在振幅变化的情况下进行地震速度分析

获得准确的速度模型在许多常规地震成像算法中起着至关重要的作用。地震速度模型通常是通过地震速度分析工作流程建立的。常规工作流程无法处理时差曲线上的极性变化。我们通过提出一个简单而强大的基于相似性的工作流程来解决这个限制，这是传统相似性功能的修改版本。相干性函数对不同的接收器集群应用相似性分析，然后对来自所有集群的相应相干性度量求平均。所提出的方法适用于任何幅度变化的情况，包括衰减和任何类别的幅度对偏移效应。所提出的工作流程的能力通过两个合成数据以及两个现场记录的公共中点道集得到了证明。我们通过将所提出方法的结果与传统速度分析的结果以及另一种为解决极性变化任务而开发的基于相似性的算法进行比较来执行精度分析。我们还通过计算和比较理论与实践之间的数学期望来研究噪声敏感性分析。