Near-surface characterisation with B3AM: case studies of 3C ambient noise beamforming from geothermal sites across Europe

The Matlab toolbox B3AM (B3AMpy for Python) for three-component beamforming of ambient noise data provides a means to characterise the seismic (noise) wavefield and image near-surface seismic properties quickly and cheaply. Provided with three-component array data, B3AM outputs dispersion curves for pro-/retrograde Rayleigh and Love waves, estimates of wavefield composition and propagation direction as a function of frequency, and can be extended for surface wave anisotropy analysis. We present recent results from seismic array data gathered at geothermal sites in the Netherlands, the UK, and Switzerland using B3AM or B3AMpy.

For the geothermal site Kwintsheul (NL), we derive a shear-velocity profile for the first 500 meters, updating an existing profile based on P velocities and regional v_p/v_s estimates. Comparing dispersion curves from beamforming to those from cross-correlation interferometry, we find that the Rayleigh first higher mode seems to provide most of the energy in the considered frequency range and that the fundamental mode can only be recovered using the beamforming scheme but not from interferometry.

Using a nodal seismic data set collected at the Eden geothermal project (Cornwall, UK), we investigate the anisotropy of the ambient noise wavefield and relate it to faults and fractures in the area. With the additional module AssessArray we estimate the effect array geometry and source distribution have on observed anisotropy. AssesArray synthesises a data set by computing (vertical component) phase shifts at each station location corresponding to a wavefield excited by a single source or multiple sources distributed randomly around the array. We then beamform the data set as we do for real data (although for 1 component only) and analyse the variation in velocity and number of detections as a function of azimuth and frequency. We find that the array design introduces frequency dependent anisotropy as well as apparent dominant directions of wave energy that align with the maximum aperture of the array. Further, we find that the number of sources used in creating the synthetic wavefield affects the observed anisotropy. In general, we observe a larger magnitude of anisotropy for a larger number of sources, i.e., for a more complex wavefield, whereas apparent anisotropy is small or not detectable for fewer sources or a single source, respectively.

For the GeoHEAT project, which explores a joint analysis of passive seismic and borehole geo-radar data for characterising and monitoring fractured geothermal systems, we implemented and tested the beamforming workflow for a novel nodal data set from the Kanton of Thurgau (CH). Besides dispersion analysis and source directionality, we consider wavefield composition and classify time windows with respect to their dominant wave type to inform and improve Green’s function recovery for ambient noise cross-correlation tomography.