Detecting and locating seismic events with using USArray as a large antenna
We design an earthquake detection and location algorithm that explores coherence and characteristic behavior of teleseismic waves recorded by a large-scale seismic network. The procedure consists of three steps. First, for every tested source location we construct a time-distance gather by computing...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2015-01-01
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| Series: | Advances in Geosciences |
| Online Access: | http://www.adv-geosci.net/40/27/2014/adgeo-40-27-2015.pdf |
| _version_ | 1818772887617667072 |
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| author | L. Retailleau N. M. Shapiro J. Guilbert M. Campillo P. Roux |
| author_facet | L. Retailleau N. M. Shapiro J. Guilbert M. Campillo P. Roux |
| author_sort | L. Retailleau |
| collection | DOAJ |
| description | We design an earthquake detection and location algorithm that explores
coherence and characteristic behavior of teleseismic waves recorded by a
large-scale seismic network. The procedure consists of three steps. First,
for every tested source location we construct a time-distance gather by
computing great-circle distances to all stations of the network and aligning
the signals respectively. Second, we use the constructed gather to compute a
Tau-P transform. For waves emitted by teleseismic sources, the amplitude of
this transform has a very characteristic behavior with maxima corresponding
to different seismic phases. Relative location of these maxima on the
time-slowness plane strongly depends on the distance to the earthquake. To
explore this dependence, in a third step, we convolve the Tau-P amplitude
with a time-slowness filter whose maxima are computed based on prediction of
a global travel-time calculator. As a result of this three-step procedure, we
obtain a function that characterizes a likelihood of occurrence of a seismic
event at a given position in space and time. We test the developed algorithm
by applying it to vertical-component records of USArray to locate a set of
earthquakes distributed around the Globe with magnitudes between 6.1 and 7.2. |
| first_indexed | 2024-12-18T10:16:30Z |
| format | Article |
| id | doaj.art-ed139e2dd0bd494a809062ba160a99bb |
| institution | Directory Open Access Journal |
| issn | 1680-7340 1680-7359 |
| language | English |
| last_indexed | 2024-12-18T10:16:30Z |
| publishDate | 2015-01-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Advances in Geosciences |
| spelling | doaj.art-ed139e2dd0bd494a809062ba160a99bb2022-12-21T21:11:17ZengCopernicus PublicationsAdvances in Geosciences1680-73401680-73592015-01-0140273010.5194/adgeo-40-27-2015Detecting and locating seismic events with using USArray as a large antennaL. Retailleau0N. M. Shapiro1J. Guilbert2M. Campillo3P. Roux4Institut de Physique du Globe de Paris, Sorbonne Paris Cité, CNRS (UMS 7154), Paris, FranceInstitut de Physique du Globe de Paris, Sorbonne Paris Cité, CNRS (UMS 7154), Paris, FranceCEA/DAM/DIF, F-91297 Arpajon, FranceInstitut des Sciences de la Terre, CNRS, Université Joseph Fournier, Grenoble, FranceInstitut des Sciences de la Terre, CNRS, Université Joseph Fournier, Grenoble, FranceWe design an earthquake detection and location algorithm that explores coherence and characteristic behavior of teleseismic waves recorded by a large-scale seismic network. The procedure consists of three steps. First, for every tested source location we construct a time-distance gather by computing great-circle distances to all stations of the network and aligning the signals respectively. Second, we use the constructed gather to compute a Tau-P transform. For waves emitted by teleseismic sources, the amplitude of this transform has a very characteristic behavior with maxima corresponding to different seismic phases. Relative location of these maxima on the time-slowness plane strongly depends on the distance to the earthquake. To explore this dependence, in a third step, we convolve the Tau-P amplitude with a time-slowness filter whose maxima are computed based on prediction of a global travel-time calculator. As a result of this three-step procedure, we obtain a function that characterizes a likelihood of occurrence of a seismic event at a given position in space and time. We test the developed algorithm by applying it to vertical-component records of USArray to locate a set of earthquakes distributed around the Globe with magnitudes between 6.1 and 7.2.http://www.adv-geosci.net/40/27/2014/adgeo-40-27-2015.pdf |
| spellingShingle | L. Retailleau N. M. Shapiro J. Guilbert M. Campillo P. Roux Detecting and locating seismic events with using USArray as a large antenna Advances in Geosciences |
| title | Detecting and locating seismic events with using USArray as a large antenna |
| title_full | Detecting and locating seismic events with using USArray as a large antenna |
| title_fullStr | Detecting and locating seismic events with using USArray as a large antenna |
| title_full_unstemmed | Detecting and locating seismic events with using USArray as a large antenna |
| title_short | Detecting and locating seismic events with using USArray as a large antenna |
| title_sort | detecting and locating seismic events with using usarray as a large antenna |
| url | http://www.adv-geosci.net/40/27/2014/adgeo-40-27-2015.pdf |
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