Articles | Volume 13, issue 11
https://doi.org/10.5194/se-13-1781-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/se-13-1781-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Upper-lithospheric structure of northeastern Venezuela from joint inversion of surface-wave dispersion and receiver functions
Geophysical Department, Spanish Navy Observatory, 11408 San Fernando, Spain
Mariano S. Arnaiz-Rodríguez
Departamento de Geofísica, Facultad de Ingeniería,
Universidad Central de Venezuela, Caracas, Venezuela
Department of Physics of the Earth and Astrophysics, Universidad
Complutense de Madrid (UCM), 28040 Madrid, Spain
Antonio Villaseñor
Institute of Marine Sciences, Pg. Marítim de la
Barceloneta, 37-49, 08003 Barcelona, Spain
Elizabeth Berg
Sandia National Laboratories, Albuquerque, New Mexico 87185, USA
Andrés Olivar-Castaño
Institute of Geosciences, University of Potsdam,
Karl-Liebknecht-Str. 24–25, Potsdam, Germany
Sergi Ventosa
Institute of Marine Sciences, Pg. Marítim de la
Barceloneta, 37-49, 08003 Barcelona, Spain
Geosciences Barcelona, Geo3Bcn CSIC, c/ Solé Sabarís sn,
Barcelona, Spain
Ana M. G. Ferreira
Department of Earth Science, University College London, Gower
Place, WC1H 6BT London, UK
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Mariano Simón Arnaiz-Rodríguez and Javier Fullea
EGUsphere, https://doi.org/10.5194/egusphere-2025-2802, https://doi.org/10.5194/egusphere-2025-2802, 2025
This preprint is open for discussion and under review for Solid Earth (SE).
Short summary
Short summary
We introduce SEITCOM-1D, a new open-source software that connects the physical and chemical structure of the Earth’s crust and mantle with seismic observations. This relationship is often difficult to model, but SEITCOM-1D simplifies the process using geophysical and thermodynamic principles. It allows scientists to explore how variations in temperature and composition influence surface wave dispersion and receiver functions, helping to interpret what seismic data reveals about Earth's interior.
Jordi Díaz, Sergi Ventosa, Martin Schimmel, Mario Ruiz, Albert Macau, Anna Gabàs, David Martí, Özgenç Akin, and Jaume Vergés
Solid Earth, 14, 499–514, https://doi.org/10.5194/se-14-499-2023, https://doi.org/10.5194/se-14-499-2023, 2023
Short summary
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We assess the capability of multiple methods based on the interpretation of seismic noise to map the basement of the Cerdanya Basin, located in the eastern Pyrenees. Basement depth estimations retrieved from the different approaches are consistent, with maximum depths reaching 700 m close to the Têt fault bounding the basin to the east. Our results prove that seismic noise analysis using high-density networks is an excellent tool to improve the geological characterization of sedimentary basins.
Alessio Spurio Mancini, Davide Piras, Ana Margarida Godinho Ferreira, Michael Paul Hobson, and Benjamin Joachimi
Solid Earth, 12, 1683–1705, https://doi.org/10.5194/se-12-1683-2021, https://doi.org/10.5194/se-12-1683-2021, 2021
Short summary
Short summary
The localization of an earthquake is affected by many uncertainties. To correctly propagate these uncertainties into an estimate of the earthquake coordinates and their associated errors, many simulations of seismic waves are needed. This operation is computationally very intensive, hindering the feasibility of this approach. In this paper, we present a series of deep-learning methods to produce accurate seismic traces in a fraction of the time needed with standard methods.
Olivier de Viron, Michel Van Camp, Alexia Grabkowiak, and Ana M. G. Ferreira
Solid Earth, 12, 1601–1634, https://doi.org/10.5194/se-12-1601-2021, https://doi.org/10.5194/se-12-1601-2021, 2021
Short summary
Short summary
As the travel time of seismic waves depends on the Earth's interior properties, seismic tomography uses it to infer the distribution of velocity anomalies, similarly to what is done in medical tomography. We propose analysing the outputs of those models using varimax principal component analysis, which results in a compressed objective representation of the model, helping analysis and comparison.
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Short summary
This paper presents a new 3D shear-wave velocity model of the lithosphere of northeastern Venezuela, including new Moho and Vp / Vs maps. Data were retrieved from land and broadband ocean bottom seismometers from the BOLIVAR experiment.
This paper presents a new 3D shear-wave velocity model of the lithosphere of northeastern...