IAG-IASPEI 2017

Presentation information

Oral

IASPEI Symposia » S21. Lithospheric structure

[S21-5] Attenuation and lithosphere structure

Fri. Aug 4, 2017 1:30 PM - 3:00 PM Room 501 (Kobe International Conference Center 5F, Room 501)

Chairs: Kevin Furlong (PennState College of Earth and Mineral Siences) , Ulrich Achauer (IPGS-EOST, University of Strasbourg)

2:15 PM - 2:30 PM

[S21-5-03] Crustal anisotropy in different tectonic regimes inferred from the stacking of radial and transverse receiver functions

Frederik Link, Georg Ruempker, Ayoub Kaviani (Goethe University Frankfurt, Frankfurt am Main, Germany)

The H-κ-stacking algorithm of Zhu and Kanamori (2000) is a standard tool to infer the thickness of the crust, H, and the average P to S-wave velocity ratio, κ. We extend their method to include anisotropic properties of the crust such as the fast-axis orientation, φ, and the percentage of anisotropy, a (Kaviani & Ruempker, 2015). The inversion involves the computation of theoretical arrival times and amplitudes for up to 20 converted phases instead of up to 5 phases in the isotropic case. These calculations are based on solving the eigenvalue problem of the anisotropic system matrix defined by Woodhouse (1974).

In the stacking algorithm we sum the amplitudes of radial and transverse receiver functions, for all events at the computed anisotropic arrival times. The stacking is performed for simple crustal models and by systematically varying the crustal parameters. The maximum of the stacking function is obtained for the model that is characterized by the parameters (H,κ,φ,a) that best explain the observed receiver functions. Application of the method to complex data sets requires additional steps to stabilize the inversion process. For example, the uncertainty of the results is estimated statistically using a selective bootstrapping analysis which only considers solutions that allow to minimize the energy on the transverse receiver-function component when applying an inverse operator to remove the effect of the shear-wave splitting.

We apply the method to recently collected data from permanent seismic networks: (1) strong anisotropy in the crust has been reported previously for seismic stations in Israel (Ruempker et al. 2003); (2) data from the permanent Swiss network will be analyzed as part of the ongoing AlpArray project; (3) an automatization of this method for its application to large data sets is currently being addressed.

We discuss our results regarding the influence of different tectonic processes on the anisotropic properties within the earth's crust.