Monitoring Fracture Saturation With Internal Seismic Sources and Twin Neural Networks-Reference-Cited by-同舟云学术

Monitoring Fracture Saturation With Internal Seismic Sources and Twin Neural Networks

Published:2022-02 Issue:2 Volume:127 Page:
ISSN:2169-9313
Container-title:Journal of Geophysical Research: Solid Earth
language:en
Short-container-title:JGR Solid Earth

Author:

Nolte D. D.¹^ORCID,Pyrak‐Nolte L. J.¹²³^ORCID

Affiliation:

1. Department of Physics and Astronomy Purdue University West Lafayette IN USA

2. Department of Earth, Atmospheric and Planetary Sciences Purdue University West Lafayette IN USA

3. Lyles School of Civil Engineering Purdue University West Lafayette IN USA

Publisher

American Geophysical Union (AGU)

Subject

Space and Planetary Science,Earth and Planetary Sciences (miscellaneous),Geochemistry and Petrology,Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021JB023005

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1. Repeating earthquakes with remarkably repeatable ruptures on the San Andreas fault at Parkfield;Abercromnie R. E.;Geophysical Research Letters,2020

2. Class-balanced siamese neural networks

3. Reverberations, coda waves and ambient noise: Correlations at the global scale and retrieval of the deep phases

4. The effect of surface roughness and mixed-mode loading on the stiffness ratio κx/κz for fractures

5. Estimating fracture orientation from elastic-wave propagation: An ultrasonic experimental approach

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