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...
Saved in:
| Date: | 2017 |
|---|---|
| Main Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
S. Subbotin Institute of Geophysics of the NAS of Ukraine
2017
|
| Subjects: | |
| Online Access: | https://journals.uran.ua/geofizicheskiy/article/view/107503 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Journal Title: | Geofizicheskiy Zhurnal |
Institution
Geofizicheskiy Zhurnal| _version_ | 1856543091023937536 |
|---|---|
| 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. |
| first_indexed | 2025-07-17T11:04:05Z |
| format | Article |
| id | journalsuranua-geofizicheskiy-article-107503 |
| institution | Geofizicheskiy Zhurnal |
| language | English |
| last_indexed | 2025-07-17T11:04:05Z |
| publishDate | 2017 |
| publisher | S. Subbotin Institute of Geophysics of the NAS of Ukraine |
| record_format | ojs |
| 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 |