From aa55869f81d6440fbafcc9f2ce0648592aabfcfc Mon Sep 17 00:00:00 2001 From: Amir Mardan <46511946+AmirMardan@users.noreply.github.com> Date: Fri, 8 Nov 2024 11:16:24 -0500 Subject: [PATCH] update doc to pgann --- docs/conf.py | 4 ++-- docs/index.rst | 24 +++++++++++----------- docs/source/readme.rst | 45 +++++++++++++++++++++++------------------- 3 files changed, 39 insertions(+), 34 deletions(-) diff --git a/docs/conf.py b/docs/conf.py index c505e5f..873a91e 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -7,7 +7,7 @@ # https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information # don't forget to change html_context['github_repo'] in bottom of this file -project = 'PINN-FWI' +project = 'PGNN-FWI' copyright = '2023, Amir Mardan' author = 'Amir Mardan' release = '0.1.0' @@ -133,6 +133,6 @@ html_context['display_github'] = True html_context['github_user'] = 'amirmardan' -html_context['github_repo'] = 'pinn_fwi' +html_context['github_repo'] = 'pgnn_fwi' html_context['github_version'] = 'main/docs/' diff --git a/docs/index.rst b/docs/index.rst index beda996..3aed158 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -1,12 +1,12 @@ -.. PINN-FWI documentation master file, created by +.. PGNN-FWI documentation master file, created by sphinx-quickstart on Thu Mar 28 00:06:12 2024. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. -PIhysics-Informed Neural Networks for Full-Waveform Inversion (PINN-FWI) +Physics-Guided Neural Networks for Full-Waveform Inversion (PGNN-FWI) ======================================================================== -PINN-FWI +PGNN-FWI ========= .. figure:: /readme_files/25231.png @@ -15,10 +15,10 @@ PINN-FWI :target: https://github.com/AmirMardan/pinn_fwi ..caption:: -This is preliminary documentation for Physics-Informed Neural Networks for Full-Waveform Inversion (PINN-FWI) +This is preliminary documentation for Physics-Guided Neural Networks for Full-Waveform Inversion (PGNN-FWI) -In this repository, I implemented the physics-informed neural network -(PINN) for full-waveform inversion. This PINN can be implemented with or +In this repository, I implemented the physics-guided neural network +(PGNN) for full-waveform inversion. This PGNN can be implemented with or without attention block. The architecture of their study is shown in the following figure. @@ -46,10 +46,10 @@ 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 PGNN- or PGANN-FWI to create an initial model and use that to perform the conventional FWI (Not available). + | 4. `pinn_fwi.ipynb `__ for performing PGNN- 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. @@ -63,7 +63,7 @@ is using the PIANN-FWI for creating only initial model. .. toctree:: :maxdepth: 1 - :caption: PINN-FWI + :caption: PGNN-FWI source/readme @@ -78,8 +78,8 @@ References: :: - @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}, diff --git a/docs/source/readme.rst b/docs/source/readme.rst index a668e55..36609a2 100644 --- a/docs/source/readme.rst +++ b/docs/source/readme.rst @@ -1,17 +1,9 @@ -PIANN-FWI for estimating the Marmousi velocity model -==================================================== +PGANN-FWI for estimating the Marmousi velocity model +=================================================== -.. figure:: /readme_files/25231.png - :width: 20 - :alt: git - :target: https://github.com/AmirMardan/pinn_fwi - - -This is preliminary documentation for Physics-Informed Neural Networks for Full-Waveform Inversion (PINN-FWI) - -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 @@ -37,18 +29,31 @@ 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. +In this repo, there are four scripts for running 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{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}, + publisher = {European Association of Geoscientists \& Engineers}, + pages = {1-5}, + doi = {} + } .. |res| image:: /readme_files/marmousi_clean.png .. |with_init| image:: /readme_files/image2024_marmousi_clean.png