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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
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.
Louis J. Lanzerotti, David J. Thomson
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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. bin Waheed, T. Alkhalifah
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A Physics-Based Emulator for the Simulation of Geophysical Mass Flows
SIAM/ASA Journal on Uncertainty Quantification, 2015Summary: Rare natural hazards such as large volcanic eruptions can cause loss of life and damage to property. With sufficient information, those charged with public safety may issue warnings of impending hazards to mitigate the hazard impact. Recent developments in modeling and simulating large geophysical mass flows can provide useful information in ...
Asif Mahmood +2 more
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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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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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Physics Bulletin, 1986
I agree with Bruce Hobbs (Physics Bulletin October 1985 p421) that a discussion meeting between the Joint Association for Geophysics and a specialist group within The Institute of Physics would be of value. It would undoubtedly assist physicists' investigations into certain geophysical problems related to, for example, solid state, solar–terrestrial ...
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I agree with Bruce Hobbs (Physics Bulletin October 1985 p421) that a discussion meeting between the Joint Association for Geophysics and a specialist group within The Institute of Physics would be of value. It would undoubtedly assist physicists' investigations into certain geophysical problems related to, for example, solid state, solar–terrestrial ...
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Simulations in Geophysics and Space Physics: Minisymposium Abstract
2007High Performance Computing (HPC) enables increasingly complex computer models of physical processes to be built. Parallel computing, adaptive grids, and other computing tools are used to solve ever larger problems, but they also increase the complexity of the software significantly and can have an impact on the reliability of the software and the ...
Mats Holmström, Kjell Rönnmark
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Review of Physics-Informed Machine Learning Inversion of Geophysical Data
GeophysicsWe review five types of physics-informed machine learning (PIML) algorithms for inversion and modeling of geophysical data. Such algorithms use the combination of a data-driven machine learning (ML) method and the equations of physics to model and/or ...
G. Schuster, Yuqing Chen, Shihang Feng
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The Role of Experimental Physical Acoustics in Geophysics
Tectonophysics, 1972Abstract In the last five years, the progress made by measurements on rocks and minerals, using physical acoustics, has been impressive. This, coupled with corresponding theoretical progress, has resulted in a number of refinements in the understanding of the structure and history of the earth's upper mantle.
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