Phase variance as a seismic quality-control attribute

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 ensembles using circular statistics. This data-driven measure quantifies localized phase dispersion without phase unwrapping, enabling analysis of local phase trends without global assumptions or wavelet models. Phase variance is computed automatically and provides frequency-by-frequency classification from coherent signal to fully randomized, noise-dominated phase. Synthetic tests confirm that phase variance reliably captures imposed phase perturbations and their frequency dependence. Application to field prestack land data shows that conventional processing reduces phase variability primarily in the low-to-intermediate frequency range and struggles within the noise cone, while the highest and lowest frequencies show little improvement. Phase variance operates automatically over the full prestack volume, frequency by frequency, providing a consistent, human-independent metric for defining effective bandwidth and supporting phase-sensitive workflows such as AVO, migration, and full-waveform inversion.