Synthetic dataset to benchmark global tomographic methods
Identifieur interne : 000303 ( Istex/Corpus ); précédent : 000302; suivant : 000304Synthetic dataset to benchmark global tomographic methods
Auteurs : Yilong Qin ; Yann Capdeville ; Valerie Maupin ; Jean-Paul MontagnerSource :
- Eos, Transactions American Geophysical Union [ 0096-3941 ] ; 2006-11-14.
Abstract
A new set of global synthetic seismograms calculated in a three‐dimensional (3‐D), heterogeneous, anisotropic, anelastic model of the Earth using the spectral element method has been released by the European network SPICE (Seismic Wave Propagation and Imaging in Complex Media: a European Network). The set consists of 7424 three‐component records with a minimum period of 32 seconds, a sampling rate of one second, and a duration of 10,500 seconds.The aim of this synthetic data set is to conduct a blind test of existing global tomographic methods based on long‐period data, in order to test how current imaging techniques are limited by approximations in theory and by the inadequacy of data quality and coverage. The correlation between modern global tomographic models is generally correct at long wavelengths, but these tomographic models are less similar at shorter wavelengths [Becker and Boschi, 2002].In order to interpret the fine details of tomographic models, it is a fundamental prerequisite to understand quantitatively the resolving properties of specific imaging algorithms. Without knowledge of the true model, it is difficult to properly evaluate the tomographic methods.
Url:
DOI: 10.1029/2006EO460004
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ISTEX:EFECDDE841440644FCCA2346B12B0BB898708454Le document en format XML
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The set consists of 7424 three‐component records with a minimum period of 32 seconds, a sampling rate of one second, and a duration of 10,500 seconds.The aim of this synthetic data set is to conduct a blind test of existing global tomographic methods based on long‐period data, in order to test how current imaging techniques are limited by approximations in theory and by the inadequacy of data quality and coverage. The correlation between modern global tomographic models is generally correct at long wavelengths, but these tomographic models are less similar at shorter wavelengths [Becker and Boschi, 2002].In order to interpret the fine details of tomographic models, it is a fundamental prerequisite to understand quantitatively the resolving properties of specific imaging algorithms. 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The set consists of 7424 three‐component records with a minimum period of 32 seconds, a sampling rate of one second, and a duration of 10,500 seconds.The aim of this synthetic data set is to conduct a blind test of existing global tomographic methods based on long‐period data, in order to test how current imaging techniques are limited by approximations in theory and by the inadequacy of data quality and coverage.</p><p xml:id="eost15724-para-0002">The correlation between modern global tomographic models is generally correct at long wavelengths, but these tomographic models are less similar at shorter wavelengths [<i>Becker and Boschi</i>, 2002].In order to interpret the fine details of tomographic models, it is a fundamental prerequisite to understand quantitatively the resolving properties of specific imaging algorithms. 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The set consists of 7424 three‐component records with a minimum period of 32 seconds, a sampling rate of one second, and a duration of 10,500 seconds.The aim of this synthetic data set is to conduct a blind test of existing global tomographic methods based on long‐period data, in order to test how current imaging techniques are limited by approximations in theory and by the inadequacy of data quality and coverage. The correlation between modern global tomographic models is generally correct at long wavelengths, but these tomographic models are less similar at shorter wavelengths [Becker and Boschi, 2002].In order to interpret the fine details of tomographic models, it is a fundamental prerequisite to understand quantitatively the resolving properties of specific imaging algorithms. 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