20 citations · 91 across the 18 of their papers we have counts for
8 papers · 1 filter
Wave-equation-based inversion with amortized variational Bayesian inference
Ali Siahkoohi, Rafael Orozco, Gabrio Rizzuti +1
Solving inverse problems involving measurement noise and modeling errors requires regularization in order to avoid data overfit. Geophysical inverse problems, in which the Earth's…
Deep Bayesian inference for seismic imaging with tasks
Ali Siahkoohi, Gabrio Rizzuti, Felix J. Herrmann
We propose to use techniques from Bayesian inference and deep neural networks to translate uncertainty in seismic imaging to uncertainty in tasks performed on the image, such as ho…
A dual formulation of wavefield reconstruction inversion for large-scale seismic inversion
Gabrio Rizzuti, Mathias Louboutin, Rongrong Wang +1
Most of the seismic inversion techniques currently proposed focus on robustness with respect to the background model choice or inaccurate physical modeling assumptions, but are not…
Parameterizing uncertainty by deep invertible networks, an application to reservoir characterization
Gabrio Rizzuti, Ali Siahkoohi, Philipp A. Witte +1
Uncertainty quantification for full-waveform inversion provides a probabilistic characterization of the ill-conditioning of the problem, comprising the sensitivity of the solution…
Extended source imaging, a unifying framework for seismic & medical imaging
Ziyi Yin, Rafael Orozco, Philipp Witte +3
We present three imaging modalities that live on the crossroads of seismic and medical imaging. Through the lens of extended source imaging, we can draw deep connections among the…
Time-domain Wavefield Reconstruction Inversion in a TTI medium
Mathias Louboutin, Gabrio Rizzuti, Felix J. Herrmann
We introduce a generalization of time-domain wavefield reconstruction inversion to anisotropic acoustic modeling. Wavefield reconstruction inversion has been extensively researched…
Uncertainty quantification in imaging and automatic horizon tracking: a Bayesian deep-prior based approach
Ali Siahkoohi, Gabrio Rizzuti, Felix J. Herrmann
In inverse problems, uncertainty quantification (UQ) deals with a probabilistic description of the solution nonuniqueness and data noise sensitivity. Setting seismic imaging into a…
Weak deep priors for seismic imaging
Ali Siahkoohi, Gabrio Rizzuti, Felix J. Herrmann
Incorporating prior knowledge on model unknowns of interest is essential when dealing with ill-posed inverse problems due to the nonuniqueness of the solution and data noise. Unfor…