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Physics-guided deep learning for seismic inversion with hybrid training and uncertainty analysis
Geophysics, 2021The determination of subsurface elastic property models is crucial in quantitative seismic data processing and interpretation. This problem is commonly solved by deterministic physical methods, such as tomography or full-waveform inversion.
Jian Sun, K. Innanen, Chao Huang
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IEEE Signal Processing Magazine, 2022
Electromagnetic (EM) imaging is widely applied in sensing for security, biomedicine, geophysics, and various industries. It is an ill-posed inverse problem whose solution is usually computationally expensive.
Rui Guo +4 more
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Electromagnetic (EM) imaging is widely applied in sensing for security, biomedicine, geophysics, and various industries. It is an ill-posed inverse problem whose solution is usually computationally expensive.
Rui Guo +4 more
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Physics-driven deep-learning inversion with application to transient electromagnetics
Geophysics, 2021Machine learning, and specifically deep-learning (DL) techniques applied to geophysical inverse problems, is an attractive subject, which has promising potential and, at the same time, presents some challenges in practical implementation.
D. Colombo +4 more
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IEEE Geoscience and Remote Sensing Letters, 2023
Solving the wave equation is an essential step in the simulation of seismic wavefields. Physics-informed neural networks (PINNs) have been widely applied in geophysics. However, there are still some challenges in solving the time-domain wave equation due
Jingbo Zou +3 more
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Solving the wave equation is an essential step in the simulation of seismic wavefields. Physics-informed neural networks (PINNs) have been widely applied in geophysics. However, there are still some challenges in solving the time-domain wave equation due
Jingbo Zou +3 more
semanticscholar +1 more source
Upwind, No More: Flexible Traveltime Solutions Using Physics-Informed Neural Networks
IEEE Transactions on Geoscience and Remote Sensing, 2022The eikonal equation plays an important role across multidisciplinary branches of science and engineering. In geophysics, the eikonal equation and its characteristics are used in addressing two fundamental questions pertaining to seismic waves: what ...
M. Taufik, U. Waheed, T. Alkhalifah
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Green’s functions for geophysics: a review
Reports on progress in physics. Physical Society, 2019The Green’s function (GF) method, which makes use of GFs, is an important and elegant tool for solving a given boundary-value problem for the differential equation from a real engineering or physical field.
E. Pan
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Time series data in geophysics/space physics
1995 International Conference on Acoustics, Speech, and Signal Processing, 2002Most geophysical and space physics data have time as one of the key variables in the data acquisition and subsequent analysis. Generally, in order to achieve physical understanding of these data, it is necessary to carry out comprehensive time series analyses.
L.J. Lanzerotti, D.J. Thomson
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Physics of the Earth and Planetary Interiors, 2019
The Gruneisen parameter, γ, conventionally written as a dimensionless combination of familiar properties, expansion coefficient, bulk modulus, density and specific heat, can also be presented in terms of elastic moduli and their pressure derivatives ...
F. Stacey, J. Hodgkinson
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The Gruneisen parameter, γ, conventionally written as a dimensionless combination of familiar properties, expansion coefficient, bulk modulus, density and specific heat, can also be presented in terms of elastic moduli and their pressure derivatives ...
F. Stacey, J. Hodgkinson
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Deep Physics-Aware Stochastic Seismic Inversion
Geophysics, 2022Seismic inversion allows the prediction of subsurface properties from seismic reflection data and is a key step in reservoir modeling and characterization.
Paula Yamada Bürkle +2 more
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