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Ambient‐field Green's functions from asynchronous seismic observations
Author(s) -
Ma Shuo,
Beroza Gregory C.
Publication year - 2012
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2011gl050755
Subject(s) - coda , seismic noise , geology , stability (learning theory) , seismology , microseism , asynchronous communication , noise (video) , green s , field (mathematics) , remote sensing , computer science , telecommunications , mathematics , artificial intelligence , mathematical analysis , machine learning , pure mathematics , image (mathematics)
We demonstrate that the coda of station‐to‐station Green's functions extracted from the ambient seismic field in southern California reach stability in the microseism band (5–10 s) after correlating six months of noise data. The coda stability makes it possible to retrieve Green's functions between stations that operate asynchronously through scattered waves as recorded by a network of fiducial stations. The Green's functions extracted from asynchronous and synchronous data have comparable quality as long as stable virtual coda are used, and both show good convergence to the Green's functions extracted from 1 year of seismic noise with ∼50 fiducial stations. This approach suggests that Green's functions can be extracted across seismic stations regardless of whether or not they are occupied simultaneously, which raises the prospect of a new mode for seismic experiments that seek to constrain Earth structure.