Seistorch: Where wave equations meets Automatic Differentiation

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

If you are interested in ...

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:

Forward modeling

Traditional	Codes	Related Papers	Notes
Simulations	click	Wang et al., 2023	Seistorch
Finite difference method	click	-	Acoustic
Pseudospectral method	click	Kosloff & Baysal	Acoustic

FWI

Traditional	Codes	Related Papers	Notes
FWI by Pytorch	click	-	Stand alone
Acoustic FWI	click	-	Seistorch, Source Encoding
Elastic FWI	click	-	Seistorch
Regularization-based FWI	click

LSRTM

Traditional	Codes	Related Papers	Notes
Acoustic LSRTM	click	Dai et al., 2010	Seistorch
Elastic LSRTM	click	Feng & Schuster, 2017	Seistorch
VTI/TTI LSRTM	click	-	Seistorch
Joint FWI&LSRTM	click	Wu et al., 2024	Seistorch
Regularization-based LSRTM	click

Inversion with Neural Networks

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 crosstalk	click	-	Stand alone Model Reparameterization(Elastic)
Siamese FWI	click	Omar et al., 2024	Stand alone
Elastic parameters crosstalk	click	Dhara & Sen	Stand alone Model Reparameterization(Elastic)

Misfit functions

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

New features:

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

Supported equations

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 TTI (2nd)	FWI/LSRTM	Liang et al., 2024	fwi click lsrtm click
qP VTI (2nd)	FWI/LSRTM	Liang et al., 2024	fwi click lsrtm 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.

To do list

SH- and Love-wave FWI(Dokter et al., 2017)

Citation

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}}

GeophyAI/seistorch