Code to partially reproduce results in "De-risking geological carbon storage from high resolution time-lapse seismic to explainable leakage detection"
Run the command below to install the required packages.
julia -e 'Pkg.add("DrWatson.jl")'
julia --project -e 'using Pkg; Pkg.instantiate()'
conda env create -f environment.yml
source activate gcs-camGenLinData.jl: script to generate time-lapse linearized data via Born modeling operators.
RTM.jl: script to run reverse-time migration (RTM) on the linearized data.
JRM.jl: script to invert the time-lapse linearized data via joint recovery model (JRM).
The experimental setup (number of sources, receivers, amount of noise etc) can be adjusted according to input keywords.
To generate a dataset for training the deep neural classifier, we provide the clusterless version of the above 3 scripts --- where you can simply run the julia scripts locally and experiments can run on multiple instances in parallel on the cloud. This needs 3 files for registry, credential, and parameter information to be stored in registryinfo.json, credentials.json, params.json files. More information can be found in AzureClusterlessHPC.jl and JUDI4Cloud.jl.
To train the network, open main.py notebook and choose gcs-cam environment as the kernel. It uses train.py and test.py modules for training and testing. The notebook contains useful comments for each section.
The software used in this repository can be modified and redistributed according to MIT license.
If you use our software for your research, please cite our preprint:
@article {yin2022TLEdgc,
title = {De-risking geological carbon storage from high resolution time-lapse seismic to explainable leakage detection},
journal = {The Leading Edge},
year = {2022},
note = {Just accepted in the January 2023 special section in seismic resolution},
month = {09},
url = {https://slim.gatech.edu/Publications/Public/Journals/TheLeadingEdge/2022/yin2022TLEdgc/paper.html},
software = {https://github.com/slimgroup/GCS-CAM},
author = {Ziyi Yin and Huseyin Tuna Erdinc and Abhinav Prakash Gahlot and Mathias Louboutin and Felix J. Herrmann}
}This package was written by Ziyi Yin, Huseyin Tuna Erdinc, Abhinav Prakash Gahlot 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.
SLIM public GitHub account, https://github.com/slimgroup.