Automatic Differentiation‐Based Full Waveform Inversion With Flexible Workflows

Abstract Full waveform inversion (FWI) is able to construct high‐resolution subsurface models by iteratively minimizing discrepancies between observed and simulated seismic data. However, its implementation can be rather involved for complex wave equations, objective functions, or regularization. Re...

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主要な著者:	Feng Liu, Haipeng Li, Guangyuan Zou, Junlun Li
フォーマット:	Artigo
言語:	Inglês
出版事項:	Wiley 2025-03-01
シリーズ:	Journal of Geophysical Research: Machine Learning and Computation
主題:	automatic differentiation full waveform inversion wave equation deep prior uncertainty estimation with dropout flexible workflow
オンライン･アクセス:	https://doi.org/10.1029/2024JH000542
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