Petroleum Science >2026, Issue6: 3248-3269 DOI: https://doi.org/10.1016/j.petsci.2026.04.013
Phase-based polarized direct envelope inversion with total variation regularization for simultaneous source seismic data: Application to SEG 2014 Chevron blind test dataset Open Access
文章信息
作者:Yong Hu, Xi-Zhu Guan, Li-Yun Fu, Yi-Bo Wang, Ru-Shan Wu
作者单位:
投稿时间:
引用方式:Hu, Y., Guan, X.Z., Fu, L.Y., et al., 2026. Phase-based polarized direct envelope inversion with total variation regularization for simultaneous source seismic data: Application to SEG 2014 Chevron blind test dataset. Petrol. Sci. 23 (6), 3248–3269. https://doi.org/10.1016/j.petsci.2026.04.013.
文章摘要
In subsalt hydrocarbon exploration, the strong velocity contrast associated with salt structures poses significant challenges to conventional full waveform inversion (FWI) method. While direct envelope inversion can invert large-scale salt dome, it fails to invert the salt-bottom velocity structures due to the absence of waveform phase information. To solve this problem, we first use a sliding Gaussian window to decompose seismic data into the local scale waveform. Subsequently, we combine the local scale envelope signal with waveform instantaneous phase to obtain the polarity envelope. The resulting polarity envelope can invert low-frequency components while preserving the phase characteristics of seismic data, enabling more accurate low-wavenumber velocity structures. Based on this, we propose a phase-based polarized direct envelope inversion with total variation regularization for simultaneous source seismic data (simultaneous source TV-PDEI) to improve the accuracy of velocity inversion, remove the crosstalk noise, and enhance the computational efficiency. Numerical experiments on salt models and Chevron blind dataset test demonstrate that the simultaneous source TV-PDEI efficiently provides a robust initial velocity model for FWI.
关键词
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Full waveform inversion; Direct envelope inversion; Polarity envelope; Chevron blind dataset test; Total variation regularization