I train a Generative Adversarial Network to produce realistic seismic wave speed models. I integrate the generator network into seismic Full-Waveform Inversion to reduce the number of model parameters and restrict the inverted models to only those that are plausible. Applying the method to a 2D section of the SEAM model, I demonstrate that it can produce more plausible results than conventional Full-Waveform Inversion.
@article{arxiv.1806.00828,
title = {Generative Adversarial Networks for Model Order Reduction in Seismic Full-Waveform Inversion},
author = {Alan Richardson},
journal= {arXiv preprint arXiv:1806.00828},
year = {2018}
}