Bayesian surface wave dispersion inversion of glaciated environments ...
<!--!introduction!--> We present a probabilistic approach to the inversion of surface wave dispersion data from glacial environments. This is intended to (i) assess non-linearity and non-uniqueness, and (ii) properly quantify resolution and trade-offs. For this, we use seismic data from Distri...
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GFZ German Research Centre for Geosciences
2023
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ftdatacite:10.57757/iugg23-1912 2023-06-11T04:12:15+02:00 Bayesian surface wave dispersion inversion of glaciated environments ... Lanteri, Ariane Gebraad, Lars Zunino, Andrea Klaasen, Sara Jonsdottir, Kristin Hofstede, Coen Eisen, Olaf Zigone, Dimitri Fichtner, Andreas 2023 https://dx.doi.org/10.57757/iugg23-1912 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5017627 unknown GFZ German Research Centre for Geosciences Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 ConferencePaper Oral Article 2023 ftdatacite https://doi.org/10.57757/iugg23-1912 2023-06-01T11:59:05Z <!--!introduction!--> We present a probabilistic approach to the inversion of surface wave dispersion data from glacial environments. This is intended to (i) assess non-linearity and non-uniqueness, and (ii) properly quantify resolution and trade-offs. For this, we use seismic data from Distributed Acoustic Sensing (DAS) experiments deployed on the Vatnajökull ice sheet located on Grímsvötn volcano in Iceland, and the Northeast Greenland Ice Stream (NEGIS). Our method is based on a regularisation-free Bayesian inference approach, implemented using a Hamiltonian Monte Carlo (HMC) algorithm. Exploiting derivative information for efficient sampling of high-dimensional model spaces, HMC approximates the posterior probability densities of all model parameters. Applied specifically to multi-mode surface wave dispersion measurements, HMC yields probabilistic models of 1-D anisotropic stratified media parameterised in terms of the P-wave velocities Vpv and Vph, the S-wave velocities Vsv and Vsh, the anisotropy ... : The 28th IUGG General Assembly (IUGG2023) (Berlin 2023) ... Conference Object Greenland Ice Sheet Iceland Vatnajökull DataCite Metadata Store (German National Library of Science and Technology) Greenland Vatnajökull ENVELOPE(-16.823,-16.823,64.420,64.420) |
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DataCite Metadata Store (German National Library of Science and Technology) |
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description |
<!--!introduction!--> We present a probabilistic approach to the inversion of surface wave dispersion data from glacial environments. This is intended to (i) assess non-linearity and non-uniqueness, and (ii) properly quantify resolution and trade-offs. For this, we use seismic data from Distributed Acoustic Sensing (DAS) experiments deployed on the Vatnajökull ice sheet located on Grímsvötn volcano in Iceland, and the Northeast Greenland Ice Stream (NEGIS). Our method is based on a regularisation-free Bayesian inference approach, implemented using a Hamiltonian Monte Carlo (HMC) algorithm. Exploiting derivative information for efficient sampling of high-dimensional model spaces, HMC approximates the posterior probability densities of all model parameters. Applied specifically to multi-mode surface wave dispersion measurements, HMC yields probabilistic models of 1-D anisotropic stratified media parameterised in terms of the P-wave velocities Vpv and Vph, the S-wave velocities Vsv and Vsh, the anisotropy ... : The 28th IUGG General Assembly (IUGG2023) (Berlin 2023) ... |
format |
Conference Object |
author |
Lanteri, Ariane Gebraad, Lars Zunino, Andrea Klaasen, Sara Jonsdottir, Kristin Hofstede, Coen Eisen, Olaf Zigone, Dimitri Fichtner, Andreas |
spellingShingle |
Lanteri, Ariane Gebraad, Lars Zunino, Andrea Klaasen, Sara Jonsdottir, Kristin Hofstede, Coen Eisen, Olaf Zigone, Dimitri Fichtner, Andreas Bayesian surface wave dispersion inversion of glaciated environments ... |
author_facet |
Lanteri, Ariane Gebraad, Lars Zunino, Andrea Klaasen, Sara Jonsdottir, Kristin Hofstede, Coen Eisen, Olaf Zigone, Dimitri Fichtner, Andreas |
author_sort |
Lanteri, Ariane |
title |
Bayesian surface wave dispersion inversion of glaciated environments ... |
title_short |
Bayesian surface wave dispersion inversion of glaciated environments ... |
title_full |
Bayesian surface wave dispersion inversion of glaciated environments ... |
title_fullStr |
Bayesian surface wave dispersion inversion of glaciated environments ... |
title_full_unstemmed |
Bayesian surface wave dispersion inversion of glaciated environments ... |
title_sort |
bayesian surface wave dispersion inversion of glaciated environments ... |
publisher |
GFZ German Research Centre for Geosciences |
publishDate |
2023 |
url |
https://dx.doi.org/10.57757/iugg23-1912 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5017627 |
long_lat |
ENVELOPE(-16.823,-16.823,64.420,64.420) |
geographic |
Greenland Vatnajökull |
geographic_facet |
Greenland Vatnajökull |
genre |
Greenland Ice Sheet Iceland Vatnajökull |
genre_facet |
Greenland Ice Sheet Iceland Vatnajökull |
op_rights |
Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_doi |
https://doi.org/10.57757/iugg23-1912 |
_version_ |
1768387979184701440 |