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AI based 1D P & S-wave Velocity Models for the Greater Alpine Region from Local Earthquake Data

Braszus, Benedikt 1; Rietbrock, Andreas ORCID iD icon 1; Haberland, Christian 2; Ryberg, Trond 2
1 Geophysikalisches Institut (GPI), Karlsruher Institut für Technologie (KIT)
2 Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum (GFZ)

Abstract (englisch):

The recent rapid improvement of machine learning techniques had a large impact on the way seismological data can be processed. During the last years several machine learning algorithms determining seismic onset times have been published facilitating the automatic picking of large data sets. Here we apply the deep neural network PhaseNet to a network of over 900 permanent and temporal broad band stations that were deployed as part of the AlpArray research initiative in the Greater Alpine Region (GAR) during 2016-2020.


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Zugehörige Institution(en) am KIT Geophysikalisches Institut (GPI)
Publikationstyp Forschungsdaten
Publikationsdatum 13.03.2024
Erstellungsdatum 01.12.2020 - 10.10.2023
Identifikator DOI: 10.35097/1965
KITopen-ID: 1000169147
Lizenz Creative Commons Namensnennung – Nicht kommerziell – Weitergabe unter gleichen Bedingungen 4.0 International
Schlagwörter 1D P & S-phase seismic velocity models
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== This file is summarizing the content of the data files in this repository published together with the article:

AI based 1D P & S-wave Velocity Models for the Greater Alpine Region from Local Earthquake Data

When you are using the data provided please cite:
Benedikt Braszus, Andreas Rietbrock, Christian Haberland, Trond Ryberg, AI based 1D P & S-wave Velocity Models for the Greater Alpine Region from Local Earthquake Data, Geophysical Journal International, 2024;, ggae077, https://doi.org/10.1093/gji/ggae077

VELOCITY FILES 

AlpsLocPS_VEL.mod       
    - VELEST model file of 'AlpsLocPS_VELEST'   (red in Fig. 6 of Braszus et al., 2024)

AlpsLocPS_McMC.mod      
    - McMC model of 'AlpsLocPS_McMC'            (orange in Fig. 6 of Braszus et al., 2024)

GAR1D_PS_VEL.mod        
    - VELEST model file of 'GAR1D_PS_VELEST'    (lime in Fig. 6 of Braszus et al., 2024)

GAR1D_PS_McMC.mod       
    - McMC model of 'GAR1D_PS_McMC'             (purple in Fig. 6 of Braszus et al., 2024)

STATION FILES 

Station corrections have to be substracted from the synthetic travel times ! 
Only stations with >= 10 observations per phase are included.
The column "station4char" contains the 4-character station name used for the VELEST inversions ( see GAR1D_PS.CNV )

AlpsLocPS_sta_cors.csv  
    - File listing station data and P- & S-phase station correction terms for the "AlpsLocPS_VELEST" and "AlpsLocPS_McMC" models after relocating all events ( see Table 2 'run2' in Braszus et al., 2024 )

GAR1D_sta_cors.csv      
    - File listing station data and P- & S-phase station correction terms for the final "GAR1D_PS_VELEST" and "GAR1D_PS_McMC" models

EVENT FILE
events_VELEST.csv

  • Catalog of relocated events using VELEST

PICK FILE

GAR1D_PS.CNV
    - .CNV file of final VELEST run yielding the GAR1D_PS_VELEST model 
    - the 4-character station names can be mapped back to the true names with the station file "GAR1D_sta_cors.csv"
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