Improved surface-wave retrieval from ambient seismic noise by multi-dimensional deconvolution

The methodology of surface‐wave retrieval from ambient seismic noise by crosscorrelation relies on the assumption that the noise field is equipartitioned. Deviations from equipartitioning degrade the accuracy of the retrieved surface‐wave Green's function. A point‐spread function, derived from...

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Bibliographic Details
Published in:Geophysical research letters 2011-01, Vol.38 (1), p.np-n/a
Main Authors: Wapenaar, Kees, Ruigrok, Elmer, van der Neut, Joost, Draganov, Deyan
Format: Article
Language:English
Subjects:
Accuracy
ambient noise
Deviation
Earth sciences
Earth, ocean, space
Exact sciences and technology
Green's function
Green's functions
Mathematical analysis
Mathematical models
Methodology
Noise
Retrieval
Seismology
surface wave
Surface waves
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Summary:The methodology of surface‐wave retrieval from ambient seismic noise by crosscorrelation relies on the assumption that the noise field is equipartitioned. Deviations from equipartitioning degrade the accuracy of the retrieved surface‐wave Green's function. A point‐spread function, derived from the same ambient noise field, quantifies the smearing in space and time of the virtual source of the Green's function. By multidimensionally deconvolving the retrieved Green's function by the point‐spread function, the virtual source becomes better focussed in space and time and hence the accuracy of the retrieved surface‐wave Green's function may improve significantly. We illustrate this at the hand of a numerical example and discuss the advantages and limitations of this new methodology.
ISSN:0094-8276
1944-8007
DOI:10.1029/2010GL045523