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Conventional full waveform inversion (FWI) using least square distance (LSD) between the observed and predicted seismograms suffers from local minima. Recently, earth mover's distance (EMD) has been introduced to FWI to compute the misfit…

Geophysics · Physics 2018-08-23 Peng Yong , Wenyuan Liao , Jianping Huang , Zhenchun Li , Yaoting Lin

We present a technique for reconstructing subsurface velocity model changes from time-lapse seismic survey data using full-waveform inversion (FWI). The technique is based on simultaneously inverting multiple survey vintages, with model…

Geophysics · Physics 2014-09-30 Musa Maharramov , Biondo Biondi

Seismic surface wave tomography uses surface wave information to obtain velocity structures in the subsurface. Due to data noise and nonlinearity of the problem, surface wave tomography often has non-unique solutions. It is therefore…

Geophysics · Physics 2025-11-06 Wenda Yang , Xin Zhang

Seismic velocity is one of the most important parameters used in seismic exploration. Accurate velocity models are key prerequisites for reverse-time migration and other high-resolution seismic imaging techniques. Such velocity information…

Geophysics · Physics 2019-02-19 Fangshu Yang , Jianwei Ma

In this paper we study two basic facts of optimal transportation on Wiener space W. Our first aim is to answer to the Monge Problem on the Wiener space endowed with the Sobolev type norm (k,gamma) to the power of p (cases p = 1 and p > 1…

Probability · Mathematics 2013-01-25 Vincent Nolot

In our paper [SIAM J.\ Appl.~Math.\ 79-6 (2019), https://doi.org/10.1137/19M1269403] we considered full waveform inversion (FWI) in the viscoelastic regime. FWI entails the nonlinear inverse problem of recovering parameter functions of the…

Analysis of PDEs · Mathematics 2022-03-03 Andreas Kirsch , Andreas Rieder

We propose a novel end-to-end non-minimax algorithm for training optimal transport mappings for the quadratic cost (Wasserstein-2 distance). The algorithm uses input convex neural networks and a cycle-consistency regularization to…

Machine Learning · Computer Science 2020-12-11 Alexander Korotin , Vage Egiazarian , Arip Asadulaev , Alexander Safin , Evgeny Burnaev

This paper introduces Wasserstein variational inference, a new form of approximate Bayesian inference based on optimal transport theory. Wasserstein variational inference uses a new family of divergences that includes both f-divergences and…

Phased array ultrasound is a widely used technique in non-destructive testing. Using piezoelectric elements as both sources and receivers provides a significant gain in information and enables more accurate defect detection. When all…

Computational Engineering, Finance, and Science · Computer Science 2026-01-13 Tim Bürchner , Simon Schmid , Lukas Bergbreiter , Ernst Rank , Stefan Kollmannsberger , Christian U. Grosse

Full waveform inversion (FWI) commonly stands for the state-of-the-art approach for imaging subsurface structures and physical parameters, however, its implementation usually faces great challenges, such as building a good initial model to…

Geophysics · Physics 2023-04-05 Jian Sun , Kristopher Innanen

We investigate here the optimal transportation problem on configuration space for the quadratic cost. It is shown that, as usual, provided that the corresponding Wasserstein is finite, there exists one unique optimal measure and that this…

Probability · Mathematics 2007-05-23 L. Decreusefond

We introduce Wasserstein-like dynamical transport distances between vector-valued densities on the real line. The mobility function from the scalar theory is replaced by a mobility matrix, that is subject to positivity and concavity…

Analysis of PDEs · Mathematics 2016-01-18 Jonathan Zinsl , Daniel Matthes

We develop the theory of a metric, which we call the $\nu$-based Wasserstein metric and denote by $W_\nu$, on the set of probability measures $\mathcal P(X)$ on a domain $X \subseteq \mathbb{R}^m$. This metric is based on a slight…

Optimization and Control · Mathematics 2022-09-16 Luca Nenna , Brendan Pass

Considering two random variables with different laws to which we only have access through finite size iid samples, we address how to reweight the first sample so that its empirical distribution converges towards the true law of the second…

Statistics Theory · Mathematics 2022-06-08 Julien Reygner , Adrien Touboul

Extended formulation of Full Waveform Inversion (FWI), called Wavefield Reconstruction Inversion (WRI), offers potential benefits of decreasing the nonlinearity of the inverse problem by replacing the explicit inverse of the ill-conditioned…

Optimization and Control · Mathematics 2020-05-18 Hossein S. Aghamiry , Ali Gholami , Stéphane Operto

We propose a methodology for intercomparing climate models and evaluating their performance against benchmarks based on the use of the Wasserstein distance (WD). This distance provides a rigorous way to measure quantitatively the difference…

Atmospheric and Oceanic Physics · Physics 2020-11-16 Gabriele Vissio , Valerio Lembo , Valerio Lucarini , Michael Ghil

Full Waveform Inversion (FWI) is a technique employed to attain a high resolution subsurface velocity model. However, FWI results are effected by the limited illumination of the model domain and the quality of that illumination, which is…

Geophysics · Physics 2024-08-20 Lingyun Yang , Omar M. Saad , Guochen Wu , Tariq Alkhalifah

The excavation process in mechanized tunneling can be improved by reconnaissance of the geology ahead. A nondestructive exploration can be achieved in means of seismic imaging. A full waveform inversion approach, which works in the…

Computational Engineering, Finance, and Science · Computer Science 2022-02-08 Christopher Riedel , Khayal Musayev , Matthias Baitsch , Klaus Hackl

A common feature of methods for analyzing samples of probability density functions is that they respect the geometry inherent to the space of densities. Once a metric is specified for this space, the Fr\'echet mean is typically used to…

Methodology · Statistics 2018-12-20 Alexander Petersen , Hans-Georg Müller

In the workflow of Full-Waveform Inversion (FWI), we often tune the parameters of the inversion to help us avoid cycle skipping and obtain high resolution models. For example, typically start by using objective functions that avoid cycle…

Geophysics · Physics 2020-02-11 Bingbing Sun , Tariq Alkhalifah