Potential geothermal reservoir systems in the Kenyan Great Rift Valley and volcanic region assessed by ambient noise analysis

Abstract

To identify potential geothermal reservoirs in the Kenyan Great Rift, we analyzed ambient noise data to reveal seismic velocities and map azimuth-based Rayleigh-wave phase velocities. We extracted phase velocity dispersion curves from the ambient noise cross-correlation using the zero-crossing method and constructed S-wave velocity models using 3D surface-wave tomography. S-wave velocities were lower under Silali and Paka volcanoes (i.e., in magmatic regions) and in fractured areas (i.e., geothermal reservoirs) normal to the rift axis. We detected magmas at depths of >3 km beneath the volcanoes. Low-velocity anomalies may be related to fluid migration pathways. Most potential geothermal reservoirs are located above magma bodies and below the rift axis and are associated with intensive fracturing and porous rocks. Our approach used a limited number of seismometers, making it useful for application in areas with restricted access and challenging deployment; therefore, it could be used for the assessment of preliminary results in other magmatically active regions.