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On The Measurement Of Seismic Travel-Time Changes In The Time-Frequency Domain With Wavelet Cross-Spectral Analysis

Shujuan Mao, Aurelien Mordret, Michel Campillo, Hongjian Fang, & Rob van der Hilst

Published August 15, 2019, SCEC Contribution #9798, 2019 SCEC Annual Meeting Poster #045

The spatial distribution of temporal variations in seismic wavespeed is key to understanding the sources and physical mechanisms of various geophysical systems. The imaging of wavespeed changes requires accurate measurements of travel-time delays with both high lapse-time and frequency resolutions. However, traditional methods for time-shifts estimation suffer from their limited resolutions. In this paper we propose a new approach, the wavelet method, to measuring the travel-time evolution in the time-frequency domain. This method is based on the wavelet cross-spectral analysis, and can provide optimal time-frequency joint resolution while being computationally efficient. It can deal not only with coda but also dispersive waves even in the presence of cycle skipping. Using synthetic coda, we show that the wavelet method can retrieve the travel-time shifts more stably and accurately than the more traditional doublet method. An application on ambient noise cross-correlations at Salton Sea Geothermal Field indicates that the wavelet method is less affected by spectral smearing and better discriminates dv/v variations in different frequency bands. Upon investigations on synthetic codas, we illustrate that the bias on dv/v measurements due to changes in sources frequency content is likely to be negligible, either with traditional methods or with the new wavelet method by coda wave interferometry. The wavelet method shows promise for seismic interferometry in monitoring applications to the aim of localizing changes in space.

Key Words
Monitoring; Ambient Noise; Seismic interferometry; Wavelet Analysis

Mao, S., Mordret, A., Campillo, M., Fang, H., & van der Hilst, R. (2019, 08). On The Measurement Of Seismic Travel-Time Changes In The Time-Frequency Domain With Wavelet Cross-Spectral Analysis . Poster Presentation at 2019 SCEC Annual Meeting.

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