Neural network modeling of Herglotz—Wiechert inversion of multiparametric travel-time curves of seismic waves

Using artificial neural networks to solve a problem of plotting travel-time curves of seismic waves can create nonlinear travel-time model of P and S phases of seismic waves arrangement as a function of several arguments: source depth, magnitude, back azimuth and epicenter distance. Construction of...

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Datum:2017
Hauptverfasser: Lazarenko, M., Herasymenko, O.
Format: Artikel
Sprache:Englisch
Veröffentlicht: S. Subbotin Institute of Geophysics of the NAS of Ukraine 2017
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Online Zugang:https://journals.uran.ua/geofizicheskiy/article/view/107503
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Geofizicheskiy Zhurnal
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author Lazarenko, M.
Herasymenko, O.
author_facet Lazarenko, M.
Herasymenko, O.
author_sort Lazarenko, M.
baseUrl_str
collection OJS
datestamp_date 2020-10-07T11:15:39Z
description Using artificial neural networks to solve a problem of plotting travel-time curves of seismic waves can create nonlinear travel-time model of P and S phases of seismic waves arrangement as a function of several arguments: source depth, magnitude, back azimuth and epicenter distance. Construction of three-dimensional travel-time relationships and their use for modeling of hadographs and their inversion are considered on examples of seismic records Ukrainian seismic stations. Examples of inversion locus within the model Herglotz—Wiechert and features of application of the model in a real environment for single seismic stations, and generalization for arbitrary coordinate of the source and the point of signal registration in the Black Sea region are given.
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spelling journalsuranua-geofizicheskiy-article-1075032020-10-07T11:15:39Z Neural network modeling of Herglotz—Wiechert inversion of multiparametric travel-time curves of seismic waves Lazarenko, M. Herasymenko, O. neural network seismic waves propagation training the Herglots—Wiechert inversion discrepancies travel-time curves velocity gradient Using artificial neural networks to solve a problem of plotting travel-time curves of seismic waves can create nonlinear travel-time model of P and S phases of seismic waves arrangement as a function of several arguments: source depth, magnitude, back azimuth and epicenter distance. Construction of three-dimensional travel-time relationships and their use for modeling of hadographs and their inversion are considered on examples of seismic records Ukrainian seismic stations. Examples of inversion locus within the model Herglotz—Wiechert and features of application of the model in a real environment for single seismic stations, and generalization for arbitrary coordinate of the source and the point of signal registration in the Black Sea region are given. S. Subbotin Institute of Geophysics of the NAS of Ukraine 2017-07-25 Article Article application/pdf https://journals.uran.ua/geofizicheskiy/article/view/107503 10.24028/gzh.0203-3100.v39i4.2017.107503 Geofizicheskiy Zhurnal; Vol. 39 No. 4 (2017); 3-14 Геофизический журнал; Том 39 № 4 (2017); 3-14 Геофізичний журнал; Том 39 № 4 (2017); 3-14 2524-1052 0203-3100 en https://journals.uran.ua/geofizicheskiy/article/view/107503/102671 Copyright (c) 2020 Geofizicheskiy Zhurnal https://creativecommons.org/licenses/by/4.0
spellingShingle neural network
seismic waves propagation
training
the Herglots—Wiechert inversion
discrepancies
travel-time curves
velocity gradient
Lazarenko, M.
Herasymenko, O.
Neural network modeling of Herglotz—Wiechert inversion of multiparametric travel-time curves of seismic waves
title Neural network modeling of Herglotz—Wiechert inversion of multiparametric travel-time curves of seismic waves
title_full Neural network modeling of Herglotz—Wiechert inversion of multiparametric travel-time curves of seismic waves
title_fullStr Neural network modeling of Herglotz—Wiechert inversion of multiparametric travel-time curves of seismic waves
title_full_unstemmed Neural network modeling of Herglotz—Wiechert inversion of multiparametric travel-time curves of seismic waves
title_short Neural network modeling of Herglotz—Wiechert inversion of multiparametric travel-time curves of seismic waves
title_sort neural network modeling of herglotz—wiechert inversion of multiparametric travel-time curves of seismic waves
topic neural network
seismic waves propagation
training
the Herglots—Wiechert inversion
discrepancies
travel-time curves
velocity gradient
topic_facet neural network
seismic waves propagation
training
the Herglots—Wiechert inversion
discrepancies
travel-time curves
velocity gradient
url https://journals.uran.ua/geofizicheskiy/article/view/107503
work_keys_str_mv AT lazarenkom neuralnetworkmodelingofherglotzwiechertinversionofmultiparametrictraveltimecurvesofseismicwaves
AT herasymenkoo neuralnetworkmodelingofherglotzwiechertinversionofmultiparametrictraveltimecurvesofseismicwaves