Author

T. Alkhalifah

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Preprint Sep 2026

Shallow-to-deep velocity model building via diffusion models-Part II: Realistic scenarios

Full-waveform inversion (FWI) requires accurate initial velocity models to avoid cycle-skipping, but constructing such models remains challenging in practice. Building on the depth-progressive diffusion framework introduced in Part~I, which relied on idealized reflectivity constraints, this work adapts the methodology...

Shi-Jun Cheng, R. Harsuko, T. Alkhalifah · 0 citations

Preprint Jul 2026

Post-FWI Injection of Learned Priors Using a Flow Matching Model

Full Waveform Inversion (FWI) is a powerful tool for subsurface velocity reconstruction but remains highly ill-posed, sensitive to acquisition limitations, often requiring some form of regularization to reduce artifacts and enhance resolution. While recent developments have shown that generative models can inject learn...

Hao Zhang, T. Alkhalifah · 0 citations

Jul 2026

Generative wave propagator

A conditional diffusion-based wavefield propagator that advances seismic wavefields recursively from one time step to the next, conditioned by a short history of recent wavefield time steps, the velocity model, and the wavefield time step index is introduced.

Shi-Jun Cheng, T. Alkhalifah · arXiv.org · 0 citations