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Locating tremor using stacked products of correlations
Author(s) -
Li Ka Lok,
Sadeghisorkhani Hamzeh,
Sgattoni Giulia,
Gudmundsson Olafur,
Roberts Roland
Publication year - 2017
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 - 10.1002/2016gl072272
Subject(s) - spurious relationship , uncorrelated , cross correlation , noise (video) , geology , hyperbola , correlation , stack (abstract data type) , algorithm , signal (programming language) , computer science , series (stratigraphy) , product (mathematics) , acoustics , mathematics , statistical physics , geometry , statistics , artificial intelligence , physics , paleontology , image (mathematics) , programming language
We introduce a back‐projection method to locate tremor sources using products of cross‐correlation envelopes of time series between seismic stations. For a given subset of n stations, we calculate the ( n − 1)th‐order product of cross‐correlation envelopes and we stack the back‐projected products over combinations of station subsets. We show that compared to existing correlation methods and for realistic signal and noise characteristics, this way of combining information can significantly reduce the effects of correlated (spurious or irrelevant signals) and uncorrelated noise. Each back‐projected product constitutes an individual localized estimate of the source locations, as opposed to a hyperbola for the existing correlation techniques, assuming a uniform velocity in two dimensions. We demonstrate the method with synthetic examples and a real‐data example from tremor at Katla Volcano, Iceland, in July 2011. Despite very complex near‐surface structure, including strong topography and thick ice cover, the method appears to produce robust estimates of tremor location.