202 citations · 715 across the 48 of their papers we have counts for
12 papers · 1 filter
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…
Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows
Ali Siahkoohi, Gabrio Rizzuti, Philipp A. Witte +1
In inverse problems, we often have access to data consisting of paired samples where are partial observations of a physical system, and represents…
Scaling through abstractions -- high-performance vectorial wave simulations for seismic inversion with Devito
Mathias Louboutin, Fabio Luporini, Philipp Witte +5
[Devito] is an open-source Python project based on domain-specific language and compiler technology. Driven by the requirements of rapid HPC applications development in exploration…
Wavefield recovery with limited-subspace weighted matrix factorizations
Yijun Zhang, Shashin Sharan, Oscar Lopez +1
Modern-day seismic imaging and monitoring technology increasingly rely on dense full-azimuth sampling. Unfortunately, the costs of acquiring densely sampled data rapidly become pro…
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…
Transfer learning in large-scale ocean bottom seismic wavefield reconstruction
Mi Zhang, Ali Siahkoohi, Felix J. Herrmann
Achieving desirable receiver sampling in ocean bottom acquisition is often not possible because of cost considerations. Assuming adequate source sampling is available, which is ach…
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…
Time-domain sparsity promoting least-squares reverse time migration with source estimation
Mengmeng Yang, Zhilong Fang, Philipp Witte +1
Least-squares reverse time migration is well-known for its capability to generate artifact-free true-amplitude subsurface images through fitting observed data in the least-squares…
A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification
Ali Siahkoohi, Gabrio Rizzuti, Felix J. Herrmann
Uncertainty quantification is essential when dealing with ill-conditioned inverse problems due to the inherent nonuniqueness of the solution. Bayesian approaches allow us to determ…