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https://github.com/slimgroup/wiser.jl

WISER: multimodal variational inference for full-waveform inversion without dimensionality reduction
https://github.com/slimgroup/wiser.jl

conditional-normalizing-flows full-waveform-inversion normalizing-flows uncertainty-quantification variational-inference

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WISER: multimodal variational inference for full-waveform inversion without dimensionality reduction

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WISER: multimodal variational inference for full-waveform inversion without dimensionality reduction



[![][license-img]][license-status]



Code to reproduce results in Ziyi Yin, Rafael Orozco, Felix J. Herrmann, "[WISER: multimodal variational inference for full-waveform inversion without dimensionality reduction](https://doi.org/10.48550/arXiv.2405.10327)". Preprint on ArXiv. DOI: 10.48550/arXiv.2405.10327



WISER is an extension to [WISE](https://doi.org/10.1190/geo2023-0744.1), published in Geophysics.



## Software descriptions



All of the software packages used in this paper are fully *open source, scalable, interoperable, and differentiable*. The readers are welcome to learn about our software design principles from [this open-access article](https://library.seg.org/doi/10.1190/tle42070474.1).



#### Wave modeling



We use [JUDI.jl](https://github.com/slimgroup/JUDI.jl) for wave modeling and inversion, which calls the highly optimized propagators of [Devito](https://www.devitoproject.org/).



#### Conditional normalizing flows



We use [InvertibleNetworks.jl] to train the conditional normalizing flows (CNFs). This package implements memory-efficient invertible networks via hand-written derivatives. This ensures that these invertible networks are scalable to realistic 3D problems.



## Installation



First, install [Julia](https://julialang.org/) and [Python](https://www.python.org/). The scripts will contain package installation commands at the beginning so the packages used in the experiments will be automatically installed.



## Scripts



[wiser.jl](scripts/wiser.jl) runs the WISER algorithm in the paper to perform physics-based latent space correction.



The script [utils.jl](scripts/utils.jl) parses the input as keywords for each experiment.



The following keyword arguments can be used to reproduce the results in the WISER paper:



- Case 1: `julia wiser.jl --lr_wiser=0.004`

- Case 2: `julia wiser.jl --test_snr=0.0 --amplitude=0.2 --lambda=10.0 --lr_pre=0.0004`



## LICENSE



The software used in this repository can be modified and redistributed according to [MIT license](LICENSE).



## Reference



If you use our software for your research, we appreciate it if you cite us following the bibtex in [CITATION.bib](CITATION.bib).



## Authors



This repository is written by [Ziyi Yin] and [Rafael Orozco] from the [Seismic Laboratory for Imaging and Modeling] (SLIM) at the Georgia Institute of Technology.



If you have any question, we welcome your contributions to our software by opening issue or pull request.



SLIM Group @ Georgia Institute of Technology, [https://slim.gatech.edu](https://slim.gatech.edu/).      

SLIM public GitHub account, [https://github.com/slimgroup](https://github.com/slimgroup).    



[license-status]:LICENSE

[license-img]:http://img.shields.io/badge/license-MIT-brightgreen.svg?style=flat?style=plastic

[Seismic Laboratory for Imaging and Modeling]:https://slim.gatech.edu/

[InvertibleNetworks.jl]:https://github.com/slimgroup/InvertibleNetworks.jl

[Ziyi Yin]:https://ziyiyin97.github.io/

[Rafael Orozco]:https://slim.gatech.edu/people/rafael-orozco