Full waveform inversion based on deep learning and the phase-preserving symplectic partitioned Runge-Kutta method

Full waveform inversion based on deep learning and the phase-preserving symplectic partitioned Runge-Kutta method

To obtain more accurate full waveform inversion results, we present a forward modeling method with minimal phase error, low numerical dispersion, and high computational efficiency. To solve the 2D acoustic wave equation, we utilize a finite-difference (FD) scheme with optimized coefficients for spat...

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Bibliographic Details
Main Authors: Yanjie Zhou, Xianxiang Leng, Xueyuan Huang, Xijun He, Tianming Cao
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-11-01
Series:Frontiers in Earth Science
Subjects:
OSPRK method
FWI
RNN
nadam optimizer
Log_Cosh loss
the physical information operator
Online Access:https://www.frontiersin.org/articles/10.3389/feart.2024.1472303/full

Internet

https://www.frontiersin.org/articles/10.3389/feart.2024.1472303/full

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