A phase unwrapping approach in measuring surface wave phase velocities from ambient noise

Author:

Xie Yanan12,Luo Yinhe13,Yang Yingjie45ORCID

Affiliation:

1. Hubei Subsurface Multi–scale Imaging Key Laboratory, School of Geophysics and Geomatics, China University of Geosciences , 388, Lumo Rd., Wuhan, Hubei 430074 , China

2. Department of Earth and Space Sciences, Southern University of Science and Technology , Shenzhen 518055 , China

3. State Key Laboratory of Geological Processes and Mineral Resources, School of Geophysics and Geomatics, China University of Geosciences , Wuhan, Hubei 430074 , China

4. Department of Earth and Space Sciences, Southern University of Science and Technology , Shenzhen 518055 , China . E-mail: yangyj@sustech.edu.cn

5. Guangdong Provincial Key Laboratory of Geophysical High-resolution Imaging Technology, Southern University of Science and Technology , Shenzhen 518055 , China

Abstract

SUMMARY In the past two decades or so, ambient noise tomography (ANT) has emerged as a powerful tool for investigating high-resolution crustal and upper-mantle structures. A crucial step in the ANT involves extracting phase velocities from cross-correlation functions (CCFs). However, obtaining precise phase velocities can be a formidable challenge, particularly when significant lateral velocity variations exist in shallow subsurface imaging that relies on short-period surface waves from ambient noise. To address this challenge, we propose an unwrapping correction method that enables the accurate extraction of short-period dispersion curves. Our method relies on the examination of the continuity of phase velocities extracted from CCFs between a common station and other neighbouring stations along a linear array. We demonstrate the effectiveness of our approach by applying our method to both synthetic and field data. Both applications suggest our unwrapping correction method can identify and correct unwrapping errors in phase velocity measurements, ensuring the extraction of accurate and reliable dispersion curves at short periods from ambient noise, which is essential for subsequent inversion for subsurface structures.

Funder

National Science Foundation of China

China University of Geosciences

Publisher

Oxford University Press (OUP)

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