Plug-and-Play regularized 3D seismic inversion with 2D pre-trained denoisers

Fuente: arXiv
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Autori principali: Luiken, Nick, Romero, Juan, Corrales, Miguel, Ravasi, Matteo
Natura: Preprint
Pubblicazione: 2024
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author Luiken, Nick
Romero, Juan
Corrales, Miguel
Ravasi, Matteo
author_facet Luiken, Nick
Romero, Juan
Corrales, Miguel
Ravasi, Matteo
contents Post-stack seismic inversion is a widely used technique to retrieve high-resolution acoustic impedance models from migrated seismic data. Its modelling operator assumes that a migrated seismic data can be generated from the convolution of a source wavelet and the time derivative of the acoustic impedance model. Given the band-limited nature of the seismic wavelet, the convolutional model acts as a filtering operator on the acoustic impedance model, thereby making the problem of retrieving acoustic impedances from seismic data ambiguous. In order to compensate for missing frequencies, post-stack seismic inversion is often regularized, meaning that prior information about the structure of the subsurface is included in the inversion process. Recently, the Plug-and-Play methodology has gained wide interest in the inverse problem community as a new form of implicit regularization, often outperforming state-of-the-art regularization. Plug-and-Play can be applied to any proximal algorithm by simply replacing the proximal operator of the regularizer with any denoiser of choice. We propose to use Plug-and-Play regularization with a 2D pre-trained, deep denoiser for 2D post-stack seismic inversion. Additionally, we show that a generalization of Plug-and-Play, called Multi-Agent Consensus Equilibrium, can be adopted to solve 3D post-stack inversion whilst leveraging the same 2D pre-trained denoiser used in the 2D case. More precisely, Multi-Agent Consensus Equilibrium combines the results of applying such 2D denoiser in the inline, crossline, and time directions in an optimal manner. We verify the proposed methods on a portion of the SEAM Phase 1 velocity model and the Sleipner field dataset. 1
format Preprint
id arxiv_https___arxiv_org_abs_2401_00753
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Plug-and-Play regularized 3D seismic inversion with 2D pre-trained denoisers
Luiken, Nick
Romero, Juan
Corrales, Miguel
Ravasi, Matteo
Geophysics
Post-stack seismic inversion is a widely used technique to retrieve high-resolution acoustic impedance models from migrated seismic data. Its modelling operator assumes that a migrated seismic data can be generated from the convolution of a source wavelet and the time derivative of the acoustic impedance model. Given the band-limited nature of the seismic wavelet, the convolutional model acts as a filtering operator on the acoustic impedance model, thereby making the problem of retrieving acoustic impedances from seismic data ambiguous. In order to compensate for missing frequencies, post-stack seismic inversion is often regularized, meaning that prior information about the structure of the subsurface is included in the inversion process. Recently, the Plug-and-Play methodology has gained wide interest in the inverse problem community as a new form of implicit regularization, often outperforming state-of-the-art regularization. Plug-and-Play can be applied to any proximal algorithm by simply replacing the proximal operator of the regularizer with any denoiser of choice. We propose to use Plug-and-Play regularization with a 2D pre-trained, deep denoiser for 2D post-stack seismic inversion. Additionally, we show that a generalization of Plug-and-Play, called Multi-Agent Consensus Equilibrium, can be adopted to solve 3D post-stack inversion whilst leveraging the same 2D pre-trained denoiser used in the 2D case. More precisely, Multi-Agent Consensus Equilibrium combines the results of applying such 2D denoiser in the inline, crossline, and time directions in an optimal manner. We verify the proposed methods on a portion of the SEAM Phase 1 velocity model and the Sleipner field dataset. 1
title Plug-and-Play regularized 3D seismic inversion with 2D pre-trained denoisers
topic Geophysics
url https://arxiv.org/abs/2401.00753