Results 211 to 220 of about 107,777 (298)

Evaluating Seismic Ambient Noise Techniques for Imaging Lava Tubes on the Moon

open access: yesJournal of Geophysical Research: Planets, Volume 131, Issue 4, April 2026.
Abstract Detecting and characterizing lava tubes is a key objective of upcoming lunar missions. While evidence for their presence exists, their precise dimensions and depths remain uncertain. This study evaluates the potential of seismic ambient noise methods, such as seismic interferometry, H/V spectral ratios, distributed acoustic sensing (DAS), and ...
Sabrina Keil   +4 more
wiley   +1 more source

Space Correlation Constrained Physics Informed Neural Network for Seismic Tomography

open access: yesJournal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.
Abstract Physics‐informed neural networks (PINNs) integrate physical constraints with neural architectures and leverage their nonlinear fitting capabilities to solve complex inverse problems. Tomography serves as a classic example, aiming to reconstruct subsurface velocity models to improve seismic exploration.
Yonghao Wang   +3 more
wiley   +1 more source

FocoNet: Transformer‐Based Focal‐Mechanism Determination

open access: yesJournal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.
Abstract Traditional focal‐mechanism determination primarily relies on fitting the first‐motion polarities with grid‐search algorithms. We developed a machine‐learning model, FocoNet, to include more seismic information into focal mechanism determination.
Xiaohan Song   +3 more
wiley   +1 more source

Seismic characterization of inland and coastal sabkhas using V<sub>P</sub>, V<sub>S</sub>, seismic anisotropy, and attenuation. [PDF]

open access: yesSci Rep
Eleslambouly A   +6 more
europepmc   +1 more source

An Effective Physics‐Informed Neural Operator Framework for Predicting Wavefields

open access: yesJournal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.
Abstract Solving the wave equation is fundamental for many geophysical applications. However, numerical solutions of the Helmholtz equation face significant computational and memory challenges. Therefore, we introduce a physics‐informed convolutional neural operator (CNO) (PICNO) to solve the Helmholtz equation efficiently.
X. Ma, T. Alkhalifah
wiley   +1 more source

GeoFWI: A Large Velocity Model Data Set for Benchmarking Full Waveform Inversion Using Deep Learning

open access: yesJournal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.
Abstract Full waveform inversion (FWI) plays an increasingly important role in the field of seismic imaging due to its strong ability to estimate subsurface properties. Specifically, data‐driven FWI (DDFWI) establishes a straightforward mapping relationship between seismic data and the corresponding velocity model, yielding promising results.
Chao Li   +5 more
wiley   +1 more source

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