Phase variance as a seismic quality-control attribute
Akshika Rohatgi, Andrey Bakulin, and Sergey Fomel

TL;DR
This paper introduces phase variance as a new, automated seismic quality-control attribute that quantifies local phase dispersion directly from seismic data, improving assessment of phase reliability especially in noisy or complex near-surface conditions.
Contribution
The paper presents a novel, data-driven method using circular statistics to measure local phase variability without phase unwrapping, applicable across full prestack volumes and frequencies.
Findings
Phase variance reliably detects imposed phase perturbations.
Conventional processing reduces phase variability mainly at low-to-intermediate frequencies.
Phase variance provides a consistent, automatic metric for phase quality assessment.
Abstract
Seismic wavefields recorded on land are strongly distorted by near-surface heterogeneity, introducing trace-specific, frequency-dependent phase perturbations that persist even after advanced time processing. Conventional surface-consistent deconvolution targets long- to mid-wavelength phase variability through overdetermination, but cannot correct localized, non-surface-consistent distortions, and its effectiveness degrades when such effects dominate, as is often the case for point-receiver data. Additionally, conventional workflows provide no direct, quantitative measure of phase reliability; phase quality is assessed only indirectly through amplitude behavior or visual inspection, leaving residual phase disorder largely undiagnosed. We introduce phase variance as a seismic quality-control attribute by treating seismic phases as circular random variables and analyzing local trace…
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Taxonomy
TopicsSeismic Imaging and Inversion Techniques · Seismic Waves and Analysis · High-pressure geophysics and materials
