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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.

Velocity analysis is an essential step in seismic reflection data processing. The conventional and fastest method to estimate how velocity changes with increasing depth is to calculate semblance coefficients. Traditional semblance has two problems: low time and velocity resolution and an inability to handle amplitude variation-with-offset (AVO) phenomenon. Although a method known as the AB semblance can arrive at peak velocities in the areas with an AVO anomaly, it has a lower velocity resolution than conventional semblance. We have developed a weighted AB semblance method that can handle both problems simultaneously. We have developed two new weighting functions to weight the AB semblance to enhance the resolution of velocity spectra in the time and velocity directions. In this way, we increase the time and velocity resolution while eliminating the AVO problem. The first weighting function is defined based on the ratio between the first and the second singular values of the time window to improve the resolution of velocity spectra in velocity direction. The second weighting function is based on the position of the seismic wavelet in the time window, thus enhancing the resolution of velocity spectra in time direction. We use synthetic and field data examples to show the superior performance of our approach over the traditional one.

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