PIFNOeikonal

This repository releases the codes related to the paper "Seismic traveltime simulation for variable velocity models using physics-informed Fourier neural operator" submitted to IEEE TGRS.

Software requirement

Python Version: 3.8.16

Pytorch Version: 2.0.0+cu117

Code explanation

PIFNO_eikonal_example.ipynb: Solving the eikonal equation using PIFNO for various models from OpenFWI.

FMM_T_T0.ipynb: Generate reference traveltimes and background traveltimes using FMM.

Overview

We have developed an innovative multi-source seismic traveltime simulation method adaptable to various velocity models, employing an advanced deep-learning technique known as the physics-informed Fourier neural operator (PIFNO). Training data from the CurveVel-A family: velocity models (first column), numerical traveltime from FMM (second column), predicted traveltime from PIFNO (third column), and traveltime difference (fourth column) for a source in the middle.

Citation information

If you find our codes and publications helpful, please kindly cite the following publications.

@article{song2024pinnpstomo,

title={Seismic traveltime simulation for variable velocity models using physics-informed Fourier neural operator},

author={Song, Chao and Zhao, Tianshuo and Bin Waheed, Umair and Liu, Cai and Tian, You},

journal={IEEE Transactions on Geoscience and Remote Sensing},

volume={62},

number={},

pages={4510909},

year={2024}

}

contact information

If there are any problems, don't hesitate to get in touch with me through my emails: [email protected];[email protected]