Seismic Waveform Inversion Toolbox

An Automatic Differentiation-based Waveform Inversion Framework Implemented in PyTorch.

Forward code for the P-SV wave equation on a staggered grid, with full waveform inversion interfaces. Finite difference approach according to stress-velocity formulation.

This repository is for PyFWI, a Python package for seismic FWI and reservoir monitoring (time-lapse FWI)

Simple frequency domain full-waveform inversion (FWI) regularized by Sobolev space norm

PGNN-FWI: performing physics-guided neural network for FWI

Radar and DC resistivity 2.5D multi-physics inversion suite. Forward modeling, separate inversions, joint inversions.

Velocity model building by deep learning. Multi-CMP gathers are mapped into velocity logs.

Official repository for the "Learned regularizations for multi-parameter elastic full waveform inversion using diffusion models" paper.

This is an open source program that contains 3D isotropic forward modeling and full waveform inversion.]

Reproducible material for A self-supervised learning framework for seismic low-frequency extrapolation

WISER: multimodal variational inference for full-waveform inversion without dimensionality reduction

WISE: full-Waveform variational Inference via Subsurface Extensions

[ICLR 2025] This is the official repository for the paper “A Unified Framework for Forward and Inverse Problems in Subsurface Imaging Using Latent Space Translations." This work proposes a generalized framework to solve forward and inverse problems, utilizing the latent space. We also propose an invertible architecture for the OpenFWI dataset.