Abstract

Accurate subsurface seismic velocities are crucial for drilling exploration wells, exploring geothermal resources, or locating seismic events. Due to their dispersive nature and prevalence in ambient seismic noise, surface wave velocities can be used to obtain shear velocities beneath seismic arrays. Localized shear velocity anomalies indicate the presence or absence of fluids; Temporal variations in shear velocities can indicate changes in fluid content or poisson ratio over time, i.e. during geothermal operations.

The 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, polarization and propagation direction as a function of frequency, and can be extended for surface wave anisotropy analysis. We will present recent examples of how these information can aid in exploring geothermal ressources.

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.