Semi-Picking: A semi-supervised arrival time picking for microseismic monitoring based on the TransUGA network combined with SimMatch

SUMMARY An accurate and efficient method for picking the first arrival of microseismic signals is crucial for processing microseismic monitoring data. However, the weak magnitude and low signal-to-noise ratio (SNR) of these signals make picking arrivals challenging. Recent advancements in deep learn...

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Bibliographic Details

Published in:	Geophysical Journal International
Main Authors:	Quanhong WANG, Guanqun Sheng, Xingong Tang, Kai Xie
Format:	Article
Language:	English
Published:	Oxford University Press 2024
Subjects:	Seismology and Earthquake Studies Seismic Imaging and Inversion Techniques Hydraulic Fracturing and Reservoir Analysis first-arrival picking microseismic monitoring semi-supervised learning TransUNet self-supervised learning self-attention low signal-to-noise ratio sample augmentation
Online Access:	https://doi.org/10.1093/gji/ggae308
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