AI RESEARCH
Improving Full Waveform Inversion in Large Model Era
arXiv CS.LG
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ArXi:2603.00377v2 Announce Type: replace Full Waveform Inversion (FWI) is a highly nonlinear and ill-posed problem that aims to recover subsurface velocity maps from surface-recorded seismic waveforms data. Existing data-driven FWI typically uses small models, as available datasets have limited volume, geological diversity, and spatial extent, leading to substantial concerns about overfitting. Although they perform well on synthetic datasets, current methods fail to generalize to realistic geological structures.