Feasibility of Deep Learning in Shear Wave Splitting analysis using Synthetic-Data Training and Waveform Deconvolution

Feasibility of Deep Learning in Shear Wave Splitting analysis using Synthetic-Data Training and Waveform Deconvolution

Teleseismic shear-wave splitting analyses are often performed by reversing the splitting process through the application of frequency- or time-domain operations aimed at minimizing the transverse-component energy of waveforms. These operations yield two splitting parameters, ɸ (fast-axis orientation...

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Bibliographic Details
Main Authors: Megha Chakraborty, Georg Rümpker, Wei Li, Johannes Faber, Nishtha Srivastava, Frederik Link
Format: Article
Language:English
Published: McGill University 2024-03-01
Series:Seismica
Subjects:
shear-wave splitting
seismic anisotropy
waveform analysis
Online Access:https://seismica.library.mcgill.ca/article/view/1124

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