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CITATION.bib
LICENSE
Manifest.toml
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WISE: full-Waveform variational Inference via Subsurface Extensions

Code to reproduce results in Ziyi Yin\*, Rafael Orozco\*, Mathias Louboutin, Felix J. Herrmann, "[WISE: full-Waveform variational Inference via Subsurface Extensions](https://arxiv.org/abs/2401.06230)". DOI: 10.48550/arXiv.2401.06230 ## 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 [gen_cig_openfwi.jl](scripts/gen_cig_openfwi.jl) generates seismic data and computes common-image gathers for the CurveFault-A velocity models in the [Open FWI dataset](https://arxiv.org/abs/2111.02926). [train_openfwi.jl](scripts/train_openfwi.jl) trains the conditional normalizing flows with pairs of velocity models and (extended) reverse-time migrations for the Open FWI dataset. [gen_cig_compass.jl](scripts/gen_cig_compass.jl) generates seismic data and computes common-image gathers for the velocity models in the [Compass dataset](https://doi.org/10.3997/2214-4609.20148575). [train_compass.jl](scripts/train_compass.jl) trains the conditional normalizing flows with pairs of velocity models and (extended) reverse-time migrations for the Compass dataset. The script [utils.jl](scripts/utils.jl) parses the input as keywords for each experiment. ## Trained networks 4 trained conditional normalizing flows can be downloaded from dropbox, with description below | Summary statistics \ dataset | Open FWI | Compass | |---------------------|----------|----------| | Reverse-time migration | [openfwi_rtm.bson](https://www.dropbox.com/scl/fi/6k77ptwot5yjwxjgfwyl1/openfwi_rtm.bson?rlkey=wcgk6ny371qahakqgqppoujvn&dl=0) | [compass_rtm.bson](https://www.dropbox.com/scl/fi/ucqpwoz9rd9uj7gnjerxp/compass_rtm.bson?rlkey=9wtxddzev2gju5jd0aoa6vhtc&dl=0) | | Common-image gathers | [openfwi_cig.bson](https://www.dropbox.com/scl/fi/k3q7vyeg7fe0z7hrho6mi/openfwi_cig.bson?rlkey=4wpeq8s9x8hs5ynde3yaitcmh&dl=0) | [compass_cig.bson](https://www.dropbox.com/scl/fi/uon81i1y2xok0wj569146/compass_cig.bson?rlkey=bo2psq4z7q00j0vo9amexuf02&dl=0) | ## 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

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