Seismic Imaging and Monitoring with Distributed Acoustic Sensing on Dark Fibers at the KIT Campus

Seismic monitoring is essential for the successful and sustainable exploration and operation of underground reservoirs and storage systems. Distributed Acoustic Sensing (DAS) has emerged as a solution for the acquisition of seismic data with high spatial density and extensive coverage, benefiting seismic monitoring efforts. Making use of unused telecommunication fibers, or dark fibers, is a particularly attractive opportunity due to the widespread availability of this infrastructure. It can help address the challenges associated with deploying and maintaining extensive seismic networks, particularly in urban areas targeted for geothermal energy development. This study uses a 3 km section of the telecommunication network at the Karlsruhe Institute of Technology (KIT) to conduct seismic monitoring near the planned DeepStor geothermal research infrastructure. The research includes a preliminary verification of the fiber's location and reports observations from local seismic events, harnessing the high spatial density of sensing points for beamforming analysis. Additionally, a signal classification framework is designed to detect and categorize frequent vehicle passages. The analysis of the associated signals makes it possible to extract virtual shot gathers. These gathers facilitate the analysis of dispersion curves at relatively high frequencies, which are subsequently used to invert shear-wave velocity profiles. This complements lower-frequency analyses derived from microseism signals during periods of minimal anthropogenic activity. Continuous seismic wavefield recordings were collected over an eight-month period, providing access to a significant time series for analysis of temporal variations and signal stacking. Our results provide a basis for future seismic monitoring of the upcoming DeepStor research infrastructure on the KIT Campus North. They also demonstrate the potential of ambient seismic wavefield analysis for advanced subsurface characterization and contribute to the broader application of DAS technology in urban seismic monitoring.