BEAT - Bayesian Earthquake Analysis Tool

Cite as:

Vasyura-Bathke, Hannes; Dettmer, Jan; Steinberg, Andreas; Heimann, Sebastian; Isken, Marius; Zielke, Olaf; Mai, Paul Martin; Sudhaus, Henriette; Jónsson, Sigurjón (2019): BEAT - Bayesian Earthquake Analysis Tool. V. 1.0. GFZ Data Services. https://doi.org/10.5880/fidgeo.2019.024

Status

I N R E V I E W : Vasyura-Bathke, Hannes; Dettmer, Jan; Steinberg, Andreas; Heimann, Sebastian; Isken, Marius; Zielke, Olaf; Mai, Paul Martin; Sudhaus, Henriette; Jónsson, Sigurjón (2019): BEAT - Bayesian Earthquake Analysis Tool. V. 1.0. GFZ Data Services. https://doi.org/10.5880/fidgeo.2019.024

Abstract

BEAT is an open-source software tool for the robust characterization of the temporal and spatial evolution of earthquake rupture processes. It uses kinematic rupture models that include low-parametric models like Moment Tensors but also complex high-parametric, finite-extent sources. In other words, BEAT allows studying earthquakes on a first-order level as points with location, size and mechanisms. In consecutive steps, the complexity of the source model may be increased by various details up to the potential to resolve rupture dimension, fault segmentation, slip-distribution and slip-history. The source model parameters and their uncertainties are estimated based on seismic waveforms, and/or geodetic observations like InSAR and GNSS data. Rapid forward modeling is enabled by using pre-computed Green's function databases, handled through the Pyrocko software library. Based on these, synthetic data are provided for arbitrary earthquake rupture models embedded in heterogeneous media. For an extensive exploration of the often high-dimensional model parameter space, BEAT offers a suite of sampling algorithms for high-standard Bayesian inference. The implementations of these sampling algorithms exploit the parallel architecture of modern computers for optimal performance. Finally, BEAT offers easy configuration and automatic visualization of relevant results. The software relies on functionality from PYROCKO (Heimann et al., 2017) and KITE (optionally, Isken et al., 2017).

Authors

Vasyura-Bathke, Hannes;University of Potsdam, Potsdam, Germany
Dettmer, Jan;University of Calgary, Calgary, Canada
Steinberg, Andreas;Christian-Albrechts-Universität zu Kiel , Kiel, Germany University
Heimann, Sebastian;GFZ German Research Centre for Geosciences, Potsdam, Germany
Isken, Marius;GFZ German Research Centre for Geosciences, Potsdam, Germany
Zielke, Olaf;KAUST King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
Mai, Paul Martin;KAUST King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
Sudhaus, Henriette;Christian-Albrechts-Universität zu Kiel , Kiel, Germany University
Jónsson, Sigurjón;KAUST King Abdullah University of Science and Technology, Thuwal, Saudi Arabia

Contact

Vasyura-Bathke, Hannes; University of Potsdam, Potsdam, Germany;
Steinberg, Andreas; Christian-Albrechts-Universität zu Kiel , Kiel, Germany University;

Keywords

Seismological, Python framework, Earthquake source parameter estimation, Bayesian Inference, Uncertainty Quantification, Finite Fault Inversion

GCMD Science Keywords

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    - subject: Earthquake source parameter estimation
    - subject: Bayesian Inference
    - subject: Uncertainty Quantification
    - subject: Finite Fault Inversion
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    - subject (subjectScheme=NASA/GCMD Earth Science Keywords): EARTH SCIENCE > SOLID EARTH > TECTONICS > VOLCANIC ACTIVITY
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