Diffraction-Angle Filtering-Based Two-Step Acoustic Full-Waveform Inversion for 3-D Seismic Reflection Data

• Published in: IEEE transactions on geoscience and remote sensing 2024-01, Vol.62, p.1-1
• Main Authors: Kim, Donggeon, Min, Dong-Joo, Oh, Ju-Won
• Format: Article
• Language: English
• Subjects: Acoustic scattering; Data models; Diving; Filtering; Filtration; Inverse problems; Kinematics; Parameter estimation; Receivers; Reflectance; Reflected waves; Reflection; Reflectivity; Scattering; Seismic data; Seismic surveys; Seismic waves; Vectors; Velocity; Wave diffraction; Wave reflection; Waveforms; Wavelengths; Waves
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2024.3374631

Full-waveform inversion (FWI) aims at building a high-resolution velocity model by fitting numerically computed seismic data to observed one. Considering both the kinematic and dynamic properties of all waves in seismic data makes FWI highly non-linear. To mitigate its non-linearity, one can preferentially build low-wavenumber background velocity first, and then retrieve high-wavenumber reflectivity. However, in the early stage of FWI, the low-wavenumber velocity update is hardly derived from the reflected waves and mainly relies on the diving waves. To secure a wider coverage of low-wavenumber velocity update from the reflected waves in addition to the diving waves, we propose two-step FWI based on diffraction-angle filtering (DAF) for 3-D seismic reflection data. In our method, DAF, which imitates the amplitude variations of the PP partial derivative wavefields with respect to the model parameters in elastic FWI to control small, intermediate or large diffraction-angle energy, is adopted for the scale separation of a given velocity model into a background velocity and reflectivity model. The prior reflectivity provides information of reflection wavepaths. Then, the low-wavenumber update generated along the full wavepaths can build a background velocity model with improved wavenumber coverage. In addition, DAF can be implemented without a large increase in computational effort, which enables practical applications of our method to large-scale 3-D seismic field data. Applications of DAF-based two-step FWI to 3-D synthetic and field seismic data demonstrate that DAF-based two-step FWI can build a reliable background velocity model, which leads to stable convergence toward the global minimum.