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Related papers: Transdimensional 2D Full-Waveform Inversion and Un…

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We propose and test the Direct Waveform Inversion (DWI) scheme to simultaneously invert for layered velocity and density profiles, using reflection seismic waveforms recorded on the surface. The recorded data include primary reflections and…

Geophysics · Physics 2021-08-10 Zhonghan Liu , Yingcai Zheng , Hua-Wei Zhou

Uncertainty quantification for full-waveform inversion provides a probabilistic characterization of the ill-conditioning of the problem, comprising the sensitivity of the solution with respect to the starting model and data noise. This…

Geophysics · Physics 2020-04-20 Gabrio Rizzuti , Ali Siahkoohi , Philipp A. Witte , Felix J. Herrmann

Edema is a potential indicator of underlying pathological changes. However, its low-contrast signature is often masked in conventional B-mode imaging by strong scatterers, making reliable detection challenging. Ultrasound (US) provides a…

Signal Processing · Electrical Eng. & Systems 2026-03-09 Ruizhi Zhang , Yhonatan Kvich , Rui Guo , Oded Cohen , Yonina C. Eldar

Accurate seismic imaging and velocity estimation are essential for subsurface characterization. Conventional inversion techniques, such as full-waveform inversion, remain computationally expensive and sensitive to initial velocity models.…

Geophysics · Physics 2025-04-23 Yunlin Zeng , Huseyin Tuna Erdinc , Rafael Orozco , Felix Herrmann

Full waveform inversion is a high-resolution subsurface imaging technique, in which full seismic waveforms are used to infer subsurface physical properties. We present a novel, target-enclosing, full-waveform inversion framework based on an…

Geophysics · Physics 2022-08-17 Polina Zheglova , Matteo Ravasi , Ivan Vasconcelos , Alison Malcolm

Seismic full-waveform inversion is a core technology for obtaining high-resolution subsurface model parameters. However, its highly nonlinear characteristics and strong dependence on the initial model often lead to the inversion process…

Machine Learning · Computer Science 2026-03-25 Caiyun Liu , Siyang Pei , Qingfeng Yu , Jie Xiong

The Bayesian inversion method demonstrates significant potential for solving inverse problems, enabling both point estimation and uncertainty quantification (UQ). However, Bayesian maximum a posteriori (MAP) estimation may become unstable…

Numerical Analysis · Mathematics 2025-06-04 Ruibiao Song , Liying Zhang

Ultrasound computed tomography (USCT) is an emerging imaging modality that holds great promise for breast imaging. Full-waveform inversion (FWI)-based image reconstruction methods incorporate accurate wave physics to produce high spatial…

Image and Video Processing · Electrical Eng. & Systems 2023-09-01 Luke Lozenski , Hanchen Wang , Fu Li , Mark A. Anastasio , Brendt Wohlberg , Youzuo Lin , Umberto Villa

Seismic tomography is a methodology to image the interior of solid or fluid media, and is often used to map properties in the subsurface of the Earth. In order to better interpret the resulting images it is important to assess imaging…

Geophysics · Physics 2020-05-20 Xin Zhang , Andrew Curtis

Quantitative speed-of-sound (SoS) and attenuation of tissues are closely related to pathology; however, conventional B-mode images are limited to qualitative visualization. Existing ultrasound full-waveform inversion (FWI) methods for…

Signal Processing · Electrical Eng. & Systems 2026-04-20 Rui Guo , Ditza Auerbach , Yonina C. Eldar

Full waveform inversion is an ill-posed inverse problem whose solution non-uniqueness -- i.e., arising from band-limited, finite-aperture, noisy data -- calls for uncertainty quantification to avoid overconfident geological interpretations.…

Geophysics · Physics 2026-03-27 Kamal Aghazade , Ali Siahkoohi , Ali Gholami

Time-lapse full-waveform inversion (FWI) has become a powerful tool for characterizing and monitoring subsurface changes in various geophysical applications. However, non-repeatability (NR) issues caused, for instance, by GPS inaccuracies,…

Geophysics · Physics 2024-07-11 Sergio Luiz E. F. da Silva , Ammir Karsou , Roger M. Moreira , Marco Cetale

We present a semi-amortized variational inference framework designed for computationally feasible uncertainty quantification in 2D full-waveform inversion to explore the multimodal posterior distribution without dimensionality reduction.…

Geophysics · Physics 2024-12-06 Ziyi Yin , Rafael Orozco , Felix J. Herrmann

We interpret uncertainty in a model for seismic wave propagation by treating the model parameters as random variables, and apply the Multilevel Monte Carlo (MLMC) method to reduce the cost of approximating expected values of selected,…

Numerical Analysis · Mathematics 2019-09-06 Marco Ballesio , Joakim Beck , Anamika Pandey , Laura Parisi , Erik von Schwerin , Raul Tempone

Iterative inversion of seismic, ultrasonic, and other wave data by local gradient-based optimization of mean-square data prediction error (Full Waveform Inversion or FWI) can fail to converge to useful model estimates if started from an…

Optimization and Control · Mathematics 2024-12-10 William W. Symes , Huiyi Chen , Susan E. Minkoff

Seismic inversion is a core problem in geophysical exploration, where traditional methods suffer from high computational costs and are susceptible to initial model dependence. In recent years, deep generative model-based seismic inversion…

Machine Learning · Computer Science 2026-03-17 Haofei Xu , Wei Cheng , Sizhe Li , Jie Xiong

We study the problem of recovering an unknown compactly-supported multivariate function from samples of its Fourier transform that are acquired nonuniformly, i.e. not necessarily on a uniform Cartesian grid. Reconstruction problems of this…

Numerical Analysis · Mathematics 2022-05-04 Ben Adcock , Milana Gataric , José Luis Romero

Implementation of the standard full waveform inversion (FWI) poses difficulties as the initial model offsets from the true model. The wavefield reconstruction inversion (WRI) was proposed to mitigate these difficulties by relaxing the…

Optimization and Control · Mathematics 2022-06-16 Ali Gholami , Hossein S. Aghamiry , Stephane Operto

The Finite Element Method (FEM) is generally unable to accurately predict natural frequencies and mode shapes of structures (eigenvalues and eigenvectors). Engineers develop numerical methods and a variety of techniques to compensate for…

Numerical Analysis · Computer Science 2015-10-16 Daniel J Joubert , Tshilidzi Marwala

Classic inversion methods adjust a model with a predefined number of parameters to the observed data. With transdimensional inversion algorithms such as the reversible-jump Markov Chain Monte Carlo (rjMCMC), it is possible to vary this…

Geophysics · Physics 2019-09-02 Márk Somogyvári , Sebastian Reich