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In seismic exploration, sources and measurements of seismic waves on the surface are used to determine model parameters representing geophysical properties of the earth. Full-waveform inversion (FWI) is a nonlinear seismic inverse technique…

Numerical Analysis · Mathematics 2019-02-05 Yunan Yang

Full waveform inversion (FWI) has recently become a favorite technique for the inverse problem of finding properties in the earth from measurements of vibrations of seismic waves on the surface. Mathematically, FWI is PDE constrained…

Numerical Analysis · Mathematics 2018-10-23 Björn Engquist , Yunan Yang

We propose the use of the Kantorovich-Rubinstein norm from optimal transport in imaging problems. In particular, we discuss a variational regularisation model endowed with a Kantorovich-Rubinstein discrepancy term and total variation…

Computer Vision and Pattern Recognition · Computer Science 2020-02-13 Jan Lellmann , Dirk A. Lorenz , Carola Schönlieb , Tuomo Valkonen

We propose a new approach to measuring the agreement between two oscillatory time series, such as seismic waveforms, and demonstrate that it can be employed effectively in inverse problems. Our approach is based on Optimal Transport theory…

Geophysics · Physics 2022-07-01 Malcolm Sambridge , Andrew Jackson , Andrew P. Valentine

Full-waveform inversion (FWI) is today a standard process for the inverse problem of seismic imaging. PDE-constrained optimization is used to determine unknown parameters in a wave equation that represent geophysical properties. The…

Numerical Analysis · Mathematics 2021-04-02 Bjorn Engquist , Yunan Yang

Seismology has been an active science for a long time. It changed character about 50 years ago when the earth's vibrations could be measured on the surface more accurately and more frequently in space and time. The full wave field could be…

Numerical Analysis · Mathematics 2018-08-15 Björn Engquist , Yunan Yang

This paper is devoted to theoretical and numerical investigation of the local minimum issue in seismic full waveform inversion (FWI). This paper provides a mathematical analysis of optimal transportation (OT) type objective function's…

Numerical Analysis · Mathematics 2021-09-01 Lingyun Qiu

Nonlinear least squares data-fitting driven by physical process simulation is a classic and widely successful technique for the solution of inverse problems in science and engineering. Known as "Full Waveform Inversion" in application to…

Optimization and Control · Mathematics 2020-10-28 William W. Symes

Wasserstein 1 optimal transport maps provide a natural correspondence between points from two probability distributions, $\mu$ and $\nu$, which is useful in many applications. Available algorithms for computing these maps do not appear to…

Optimization and Control · Mathematics 2022-11-03 Tristan Milne , Étienne Bilocq , Adrian Nachman

Full-waveform inversion (FWI) is known as a seismic data processing method that achieves high-resolution imaging. In the inversion part of the method that brings high resolution in finding a convergence point in the model space, a local…

Geophysics · Physics 2023-07-11 Jiahang Li , Hitoshi Mikada , Junichi Takekawa

Full waveform inversion is a successful procedure for determining properties of the earth from surface measurements in seismology. This inverse problem is solved by a PDE constrained optimization where unknown coefficients in a computed…

Geophysics · Physics 2016-04-19 Bjorn Engquist , Brittany D. Froese , Yunan Yang

We consider the high-resolution seismic imaging method called full-waveform inversion (FWI). FWI is a data fitting method aimed at inverting for subsurface mechanical parameters. Despite the large adoption of FWI by the academic and…

Full waveform inversion (FWI) is an important and popular technique in subsurface earth property estimation. However, using the least-squares norm in the misfit function often leads to the local minimum solution of the optimization problem,…

Numerical Analysis · Mathematics 2021-04-06 Da Li , Michael P. Lamoureux , Wenyuan Liao

Multi-marginal optimal transport enables one to compare multiple probability measures, which increasingly finds application in multi-task learning problems. One practical limitation of multi-marginal transport is computational scalability…

Conventional full-waveform inversion (FWI) using the least-squares norm ($L^2$) as a misfit function is known to suffer from cycle skipping. This increases the risk of computing a local rather than the global minimum of the misfit. In our…

Geophysics · Physics 2017-05-12 Yunan Yang , Björn Engquist , Junzhe Sun , Brittany D. Froese

We develop a general mathematical framework for variational problems where the unknown function assumes values in the space of probability measures on some metric space. We study weak and strong topologies and define a total variation…

Numerical Analysis · Mathematics 2018-06-12 Thomas Vogt , Jan Lellmann

Suppose we are given two metric spaces and a family of continuous transformations from one to the other. Given a probability distribution on each of these two spaces - namely the source and the target measures - the Wasserstein alignment…

Probability · Mathematics 2025-03-11 Soumik Pal , Bodhisattva Sen , Ting-Kam Leonard Wong

This article presents a new class of distances between arbitrary nonnegative Radon measures inspired by optimal transport. These distances are defined by two equivalent alternative formulations: (i) a dynamic formulation defining the…

Optimization and Control · Mathematics 2019-02-12 Lenaic Chizat , Gabriel Peyré , Bernhard Schmitzer , François-Xavier Vialard

Full--waveform inversion (FWI) is a method used to determine properties of the Earth from information on the surface. We use the squared Wasserstein distance (squared $W_2$ distance) as an objective function to invert for the velocity of…

Geophysics · Physics 2021-09-14 Srinath Mahankali

In this paper we propose and study a novel optimal transport based regularization of linear dynamic inverse problems. The considered inverse problems aim at recovering a measure valued curve and are dynamic in the sense that (i) the…

Functional Analysis · Mathematics 2023-04-26 Kristian Bredies , Silvio Fanzon
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