Probabilistic Inversion with Flow Matching
Machine Learning
2026-06-30 v1 Probability
Geophysics
Abstract
We demonstrate the application of Flow Matching, a technique originating from generative Artificial Intelligence, to probabilistic inversion in geophysical settings, such as seismic Full-Waveform inversion. We adapt the well-established mathematical theory of Flow Matching from generative Artificial Intelligence to the context of probabilistic inversion. We evaluate the approach with two case studies: a simple 2D velocity model to illustrate the general features of the method, and the OpenFWI dataset to show its capabilities for probabilistic inversion of more complex seismic velocity models.
Cite
@article{arxiv.2606.31288,
title = {Probabilistic Inversion with Flow Matching},
author = {Baldur Paulwitz and Stefan Buske},
journal= {arXiv preprint arXiv:2606.31288},
year = {2026}
}