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Understanding seismic body waves retrieved from noise correlations : Toward a passive deep Earth imaging
Lei Li

Understanding seismic body waves retrieved from noise correlations : Toward a passive deep Earth imaging

Author / Organization:
Science & Mathematics Published 2018 Verification Pending

Overview & Synopsis

This work aims toward an improved understanding of the seismic signals derived from the inter-receiver correlation functions of seismic noise, which is valuable and critical for a reliable noise-based deep Earth imaging. The thesis consists of seven chapters. Chapter 1 introduces background knowledge on seismic noise, from its classifications to various origins. Chapter 2 provides a literature overview on the history and development of the emerging noise correlation method, and reviews various techniques for the pre-processing of seismic noise data and post-processing of noise correlation functions. Statistics-based noise processing methods and a modified scheme for computing correlation function are developed in this chapter. Chapter 3 proposes several Radon-based techniques to analyze the slownesses of correlated wavefields and to unveil the origin of noise-derived seismic signals. Chapter 4 shows that body waves penetrating into deep Earth can be extracted from noise correlations at teleseismic distances, with noise records from two regional seismic networks. Chapter 5 applies the techniques proposed in chapter 3 to the double-array nose correlations computed in chapter 4, and accordingly reveals the origin of an early spurious phase observed in chapter 4. Chapter 6 discusses several situations that bring ambiguities into the noise-derived seismic signals and can potentially bias the noise-based imaging of subsurface structure. The last chapter provides a summarization over the contributions of this thesis and an outlook of several ongoing and prospected works.

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Document Information

Document Title Understanding seismic body waves retrieved from noise correlations : Toward a passive deep Earth imaging
Author / Organization Lei Li
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2018
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-211841
Original Source Link Visit Source Page on hal.science »