Seismic noise cross correlation studies are of increasing importance in the seismological research community due to the ubiquity of noise sources and advances on how to use the seismic noise wave field for structural imaging and monitoring purposes. Stacks of noise cross correlations are now routinely used to extract empirical Green's functions between station pairs. In regional and global scale studies, mostly surface waves are extracted due to their dominance in seismic noise wave fields. Group arrival times measured from the time-frequency representation of frequency dispersive surface waves are further used in tomographic inversions to image seismic structure. Often, the group arrivals are not clearly identified or ambiguous depending on the signal and noise characteristics. Here, we present a procedure to robustly measure group velocities using the time-frequency domain phase-weighted stack (PWS) combined with data resampling and decision strategies. The time-frequency PWS improves signal extraction through incoherent signal attenuation during the stack of the noise cross correlations. Resampling strategies help to identify signals robust against data variations and to assess their errors. We have gathered these ingredients in an algorithm where the decision strategies and tuning parameters are reduced for semiautomated processing schemes. Our numerical and field data examples show a robust assignment of surface-wave group arrivals. The method is computational efficient thanks to an implementation based on pseudoanalytic frames of wavelets and enables processing large amounts of data.

This work was supported in part by the Project MISTERIOS under Grant CGL2013-48601-C2-1-R, in part by the MIMOSA under Grant ANR-14-CE01-0012, in part by the COST Action ES1401 TIDES, in part by AGAUR, and in part by the FP7 Marie Curie Project through SV's Beatriu de Pinos Fellowship under Contract 600385. This is IPGP contribution 3814.

Peer reviewed