diff --git a/readme.rst b/readme.rst index da6ba2f..36609a2 100644 --- a/readme.rst +++ b/readme.rst @@ -1,9 +1,9 @@ -PIANN-FWI for estimating the Marmousi velocity model +PGANN-FWI for estimating the Marmousi velocity model =================================================== -In this repository, I implemented the physics-informed neural network -(PINN) for full-waveform inversion. This PINN can be implemented with or -without attention block. The architecture of their study is shown in the +In this repository, I implemented the physics-guided neural network +(PGNN) for full-waveform inversion. This PGNN can be implemented with or +without an attention block. The architecture of their study is shown in the following figure. .. figure:: /readme_files/architecture.png @@ -30,24 +30,23 @@ specified versions to be sure everything works. pip install -r requirements.txt In this repo, there are four scripts for running FWI: - | 1. `pinn_fwi.py `__ for performing PINN- or PIANN-FWI. + | 1. `pinn_fwi.py `__ for performing PGNN- or PGANN-FWI. | 2. `original_fwi.py `__ for running the conventional FWI (Not available). - | 3. `pinn_for_init.py `__ for performing PINN- or PIANN-FWI to create an initial model and use that to perform the conventional FWI (Not available). - | 4. `pinn_fwi.ipynb `__ for performing PINN- or PIANN-FWI, but this notebook might not be updated. + | 3. `pinn_for_init.py `__ for performing PINN- or PGANN-FWI to create an initial model and use that to perform the conventional FWI (Not available). + | 4. `pinn_fwi.ipynb `__ for performing PINN- or PGANN-FWI, but this notebook might not be updated. -The result of running this code for 22 shots with 2500 epochs on the -Marmousi model is shown in the following figures. +The result of running this code for 22 shots with 2500 epochs on the Marmousi model is shown in the following figures. |res| For a faster convergence (300 epochs), I considered geophones around the model and the results are |with_init| where the hybrid method -is using the PIANN-FWI for creating only initial model. +is using the PGANN-FWI for creating only the initial model. Reference: :: - @inproceedings{mardan2024piann_eage, - title = {Physics-informed attention-based neural networks for full-waveform inversion}, + @inproceedings{mardan2024pgann_eage, + title = {Physics-guided attention-based neural networks for full-waveform inversion}, author = {Mardan, Amir and Fabien-Ouellet, Gabriel}, year = {2024}, booktitle = {85$^{th}$ {EAGE} Annual Conference \& Exhibition},