EGU2020-13379
https://doi.org/10.5194/egusphere-egu2020-13379
EGU General Assembly 2020
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Joint seismic and geodetic transdimensional earthquake source optimization guided by multi-array teleseismic backprojection

Andreas Steinberg1,2, Henriette Sudhaus1, Frank Krüger3, Hannes Vasyura-Bathke3, Simon Daout4, and Marius Paul Isken1
Andreas Steinberg et al.
  • 1Kiel University, Kiel, Germany (andreas.steinberg@ifg.uni-kiel.de)
  • 2Federal Institute for Geosciences and Natural Resources, Hannover, Germany (andreas.steinberg@bgr.de)
  • 3Institute of Geosciences, University of Potsdam, Potsdam, Germany
  • 4Department of Earth Sciences, University of Oxford, Oxford, United Kingdom

Earthquakes have been observed to initiate and terminate near geometrical irregularities (bends, step-overs, branching of secondary faults). Rupture segmentationinfluences the seismic radiation and therefore, the related seismic hazard. Good imaging of rupture segmentation helps to characterize fault geometries at depth for follow-up tectonic, stress-field or other analyses. From reported earthquake source models it appears that large earthquakes with magnitudes above 7 are most often segmented, while earthquakes with magnitudes below 6.5 most often are not. If this observationreflects nature or if it is rather an artifact of our abilities to well observe and infer earthquake sources can not be answered without an objective strategy to constrain rupture complexity. However, data-driven analyses of rupture segmentation are not often conducted in source modeling as it is mostly pre-defined through a given and fixed number of sources. 

We, here, propose a segmentation-sensitive source analysis by combining a model-independent teleseismic back-projection and image segmentation methods with a kinematic fault inversion. Our approach is twofold. We first develop a time-domain multi-array back-projection of teleseismic data with robust estimations of uncertainties based on bootstrapping of the travel-time models and array weights (Palantiri software, https://braunfuss.github.io/Palantiri/). Backprojection has proven to be a powerful tool to infer rupture propagation from teleseismic data and identify irregularities of the rupture process over time.

We then model the earthquake sources with the results obtained from the backprojection and additional information obtained from the application of image segmentation methods to the InSAR displacement maps. For this second step, we use a combination of different observations (teleseismic waveforms and surface displacement maps based on InSAR) to increase the resolution on the spatio-temporal evolution of fault slip. We develop a novel Informational criterion based transdimensional optimization scheme to model an adequate representation of the source complexity. We present our method on two cases study: the 2016 Muji Mw 6.7 earthquake (Pamir) and the 2008-2009 Qaidam (Tibet) sequence of earthquakes. We find that the 2008 Qaidam earthquake ruptures one segment, the 2016 Muji earthquake on two segments and the Qaidam 2009 earthquake on two or three segments.

This work is based on the open-source, python-based Pyrocko toolbox and is conducted within the project “Bridging Geodesy and Seismology” (www.bridges.uni-kiel.de<http://www.bridges.uni-kiel.de>) funded by the DFG through an Emmy-Noether grant.

 

How to cite: Steinberg, A., Sudhaus, H., Krüger, F., Vasyura-Bathke, H., Daout, S., and Isken, M. P.: Joint seismic and geodetic transdimensional earthquake source optimization guided by multi-array teleseismic backprojection, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13379, https://doi.org/10.5194/egusphere-egu2020-13379, 2020.