Reproducible material for FreqSiameseFWI: A Novel Deep Learning Framework for Multi-Source Full Wave Inversion - Omar M. Saad and Tariq Alkhalifah

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Project structure

This repository is organized as follows:

• 📂 asset: folder containing logo;
• 📂 data: folder containing Marmousi2 and overthrust models data;
• 📂 utils: set of common function to run FWI;
• 📂 Model: containing FreqSiamese network;
• 📂 results: containing the reconstructed velocity model using FreqSiameseFWI;

Notebooks

The following notebooks are provided:

• 📙 FreqSiameseFWI_Marmousi_FWI.ipynb: the main notebook performing the FreqSiameseFWI for Marmousi model;
• 📙 FreqSiameseFWI_overethrust_FWI.ipynb: the main notebook performing the FreqSiameseFWI for overthrust model;
• 📙 FreqSiameseFWI_Marmousi_MSFWI.ipynb: the main notebook performing the FreqSiameseFWI for Marmousi model (multi-sources);
• 📙 FreqSiameseFWI_overethrust_MSFWI.ipynb: the main notebook performing the FreqSiameseFWI for overthrust model (multi-sources);

Getting started 👾 🤖

• To ensure the reproducibility of the results, we suggest using the FWIGAN.yml file when creating an environment.
• Please install the Deepwave 0.0.8 toolbox version, which is used in this project. Run:

./install_env.sh

It will take some time, but if you see the word Done! on your terminal you are ready to go.

Remember to always activate the environment by typing:

conda activate FWIGAN

Disclaimer: All experiments have been carried on a Intel(R) Xeon(R) CPU @ 2.10GHz equipped with a single NVIDIA GEForce RTX 3090 GPU. Different environment configurations may be required for different combinations of workstation and GPU.

Cite us

@article{saad2025f,
  title={F-SiameseFWI: A Novel Deep Learning Framework for Multi-Source Full Wave Inversion},
  author={Saad, Omar M and Alkhalifah, Tariq},
  journal={Geophysics},
  volume={90},
  number={4},
  pages={1--51},
  year={2025},
  doi ={https://doi.org/10.1190/geo2024-0785.1},
  publisher={Society of Exploration Geophysicists}
}