From this version, seistorch will use 'torchrun' to perform distributed full waveform inversion('mpi4py' used before). Please refer to <seistorch/examples/check_features/torchrun_dist>. The old mpi4py APIs in seistorch will be deprecated, nccl/mpi in torch will be prefered.
Inversion Tests | Status |
---|---|
Acoustic | Passed |
Acoustic+NN | Passed |
Elastic | Passed |
Others | Not test yet |
I reproduced the results of the following papers using Seistorch and some stand alone codes. If you are interested in these topics, please refer to the following links:
Traditional | Codes | Related Papers | Notes |
---|---|---|---|
FWI by Pytorch | click | - | Stand alone |
Simulations | click | Wang et al., 2023 | Seistorch |
Finite difference method | click | - | Acoustic |
Pseudospectral method | click | Kosloff & Baysal | Acoustic |
Acoustic LSRTM | click | Dai et al., 2010 | Seistorch |
Elastic LSRTM | click | Feng & Schuster, 2017 | Seistorch |
Acoustic FWI | click | - | Seistorch, Source Encoding |
Elastic FWI | click | - | Seistorch |
Joint FWI&LSRTM | click | Wu et al., 2024 | Seistorch |
FWI+NeuralNetworks | Codes | Related Papers | Notes |
---|---|---|---|
PINN | click | Majid et al., 2022 | Stand alone |
Implicit FWI | click | Sun et al., 2023 | Stand alone Model Reparameterization(Acoustic) |
Physics-guided NN FWI | click | Dhara & Sen, 2022 | Stand alone Model Reparameterization(Acoustic) |
Elastic Parameters decouple | click | - | Stand alone Model Reparameterization(Elastic) |
Siamese FWI | click | Omar et al., 2024 | Stand alone |
Elastic Parameters decouple | click | Dhara & Sen | Stand alone Model Reparameterization(Elastic) |
Misfits | Examples | Related Papers | Notes |
---|---|---|---|
Optimal Transport | click | Yang & Ma, 2023 Yang & Enguist |
- |
Envelope | click | Chi et al., 2014 Wu et al., 2014 |
- |
Traveltime | click | Wang et al., 2024 | Differentiable |
Cosine Similarity | click | Choi & Alkhalifah, 2012 Liu et al., 2016 |
Global correlation Normalized zero-lag cross-correlation |
L1 | click | ||
Local coherence | click | Yu et al., 2023 | |
Instantaneous Phase | click | Bozdag et al., 2011 Yuan et al., 2020 |
|
Weighted loss | click | Song et al., 2023 | |
Envelope Cosine Similarity | * | Oh and Alkhalifah, 2018 | Envelope-based Global Correlation Norm |
Soft Dynamic Time warpping | click | Maghoumi, 2020 Maghoumi et al., 2020 |
Type | New | Old |
---|---|---|
Weighted loss | Inspired by Song et al., 2023 | |
Boundary conditions | HABC(Xie et al.) | PML |
Distributed FWI | torchrun | mpi4py |
Anisotropic FWI | None | |
LSRTM | Elastic Feng & Schuster | None |
LSRTM | Acoustic Dai et al. | None |
EQUATIONS | USAGE | REFERENCES | EQUATION CODES |
---|---|---|---|
Scalar Acoustic (2nd) | FWI | * | PML version HABC version |
Scalar Acoustic (2nd) | LSRTM | Dai et al., 2010 | click |
Acoustic (1st) | FWI | * | click |
Variable Density (2nd) | FWI | Whitmore et al., 2020 | click |
Joint FWI & LSRTM | FWI+LSRTM | Wu et al., 2024 | click |
qP VTI (2nd) | FWI | Liang et al., 2024 | click |
qP TTI (2nd) | FWI | Liang et al., 2024 | click |
ViscoAcoustic (2nd) | FWI | Li et al., 2016 | click |
VTI (2nd) | FWI | Zhou et al., 2006 | click |
Elastic (1st) | FWI | Virieux, 1986 | click |
Elastic (1st) | LSRTM | Feng & Schuster, 2017 | click |
TTI-Elastic (1st) | FWI | * | click |
Acoustic-Elastic coupled (1st) | FWI | Yu et al., 2016 | click |
Velocity-Dilatation-Rotation (1st) | FWI | Tang et al., 2016 | click |
Note: 2nd means displacement equations, 1st means velocity-stress equations.
If you find this work useful for your research, please consider citing our paper Memory Optimization in RNN-based Full Waveform Inversion using Boundary Saving Wavefield Reconstruction:
@ARTICLE{10256076,
author={Wang, Shaowen and Jiang, Yong and Song, Peng and Tan, Jun and Liu, Zhaolun and He, Bingshou},
journal={IEEE Transactions on Geoscience and Remote Sensing},
title={Memory Optimization in RNN-based Full Waveform Inversion using Boundary Saving Wavefield Reconstruction},
year={2023},
volume={61},
number={},
pages={1-1},
doi={10.1109/TGRS.2023.3317529}}