Copertina

Robust Full Waveform Inversion with deep Hessian deblurring

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Alfarhan, Mustafa, Ravasi, Matteo, Chen, Fuqiang, Alkhalifah, Tariq
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Geophysics
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

A Deep Learning-based time shift objective function for Full Waveform Inversion
di: Alfarhan, Mustafa, et al.
Pubblicazione: (2025)

A Deep Learning‐Based Time Shift Objective Function for Full Waveform Inversion
di: Mustafa Alfarhan, et al.
Pubblicazione: (2026)

Diffusion Model-Based Posterior Sampling in Full Waveform Inversion
di: Taufik, Mohammad H., et al.
Pubblicazione: (2025)

Conditional Image Prior for Uncertainty Quantification in Full Waveform Inversion
di: Yang, Lingyun, et al.
Pubblicazione: (2024)

Efficient Upside-Down Rayleigh-Marchenko Imaging through Self-Supervised Focusing Function Estimation
di: Wang, Ning, et al.
Pubblicazione: (2025)

DiffusionInv: Prior-enhanced Bayesian Full Waveform Inversion using Diffusion models
di: Li, Yuanyuan, et al.
Pubblicazione: (2025)

Slope assisted Physics‐informed neural networks for seismic signal separation with applications on ground roll removal and interpolation
di: Francesco Brandolin, et al.
Pubblicazione: (2025)

Signal Enhancement in Distributed Acoustic Sensing Data Using a Guided Unsupervised Deep Learning Network
di: Saad, Omar M., et al.
Pubblicazione: (2024)

Reciprocity-aware adaptive tile low-rank factorization for large-scale 3D multidimensional deconvolution
di: Chen, Fuqiang, et al.
Pubblicazione: (2024)

A reciprocity-aware, low-rank regularization for multidimensional deconvolution
di: Chen, Fuqiang, et al.
Pubblicazione: (2023)

Annealed Stein Variational Gradient Descent for Improved Uncertainty Estimation in Full-Waveform Inversion
di: Corrales, Miguel, et al.
Pubblicazione: (2024)

Deep Reparameterization for Full Waveform Inversion: Architecture Benchmarking, Robust Inversion, and Multiphysics Extension
di: Liu, Feng, et al.
Pubblicazione: (2025)

Seis2Rock: A Data-Driven Approach to Direct Petrophysical Inversion of Pre-Stack Seismic Data
di: Corrales, Miguel, et al.
Pubblicazione: (2023)

Meta-PINN: Meta learning for improved neural network wavefield solutions
di: Cheng, Shijun, et al.
Pubblicazione: (2024)

Learned frequency-domain scattered wavefield solutions using neural operators
di: Huang, Xinquan, et al.
Pubblicazione: (2024)

Discovery of physically interpretable wave equations
di: Cheng, Shijun, et al.
Pubblicazione: (2024)

Velocity Model Building and Editing with Guided Denoising Diffusion Implicit Models
di: Brandolin, Francesco, et al.
Pubblicazione: (2026)

Velocity model building from seismic images using a Convolutional Neural Operator
di: Ma, Xiao, et al.
Pubblicazione: (2025)

A Deep-Learning-Driven Optimization-Based Inverse Solver for Accelerating the Marchenko Method
di: Wang, Ning, et al.
Pubblicazione: (2025)

Full waveform inversion with CNN-based velocity representation extension
di: Mu, Xinru, et al.
Pubblicazione: (2025)

Fast and Automatic Full Waveform Inversion by Dual Augmented Lagrangian
di: Aghazade, Kamal, et al.
Pubblicazione: (2024)

Linearised versus Nonlinear Estimates of Uncertainty in Full Waveform Inversion
di: Zhao, Xuebin, et al.
Pubblicazione: (2026)

Geophysical inverse problems with measurement-guided diffusion models
di: Ravasi, Matteo
Pubblicazione: (2025)

An efficient pseudoelastic pure P‐mode wave equation and the implementation of the free surface boundary condition
di: Xinru Mu, et al.
Pubblicazione: (2024)

A Deep‐Learning‐Driven Optimization‐Based Inverse Solver for Accelerating the Marchenko Method
di: Ning Wang, et al.
Pubblicazione: (2025)

Dimensionality Reduction in Full‐Waveform Inversion Uncertainty Analysis
di: W. A. Mulder, et al.
Pubblicazione: (2025)

Accurate and Robust Full Waveform Inversion Driven by Poisson Flow Generative Model Priors
di: Han Wang, et al.
Pubblicazione: (2026)

Upside down Rayleigh-Marchenko: a practical, yet exact redatuming scheme for seabed seismic acquisitions
di: Wang, Ning, et al.
Pubblicazione: (2024)

Viscoelastic Multiparameter Full Waveform Inversion Using OBN Data
di: Li Han, et al.
Pubblicazione: (2026)

GaborPINN: Efficient physics informed neural networks using multiplicative filtered networks
di: Huang, Xinquan, et al.
Pubblicazione: (2023)

Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network
di: Cheng, Shijun, et al.
Pubblicazione: (2025)

Propagating the prior from far to near offset: A self-supervised diffusion framework for progressively recovering near-offsets of towed-streamer data
di: Cheng, Shijun, et al.
Pubblicazione: (2026)

An effective physics-informed neural operator framework for predicting wavefields
di: Ma, Xiao, et al.
Pubblicazione: (2025)

Ambient Noise Full Waveform Inversion with Neural Operators
di: Zou, Caifeng, et al.
Pubblicazione: (2025)

Efficient Bayesian Full Waveform Inversion and Analysis of Prior Hypotheses in 3D
di: Zhao, Xuebin, et al.
Pubblicazione: (2024)

Physics-informed conditional diffusion model for generalizable elastic wave-mode separation
di: Cheng, Shijun, et al.
Pubblicazione: (2025)

High-resolution velocity model estimation with neural operator and the time-shift imaging condition
di: Ma, Xiao, et al.
Pubblicazione: (2025)

Self-supervised surface-related multiple suppression with multidimensional convolution
di: Cheng, Shijun, et al.
Pubblicazione: (2025)

SeparationPINN: Physics-Informed Neural Networks for Seismic P- and S-Wave Mode Separation
di: Mu, Xinru, et al.
Pubblicazione: (2025)

Propagating the prior from shallow to deep with a pre-trained velocity-model Generative Transformer network
di: Harsuko, Randy, et al.
Pubblicazione: (2024)