Performance Assessment of Distributed Acoustic Sensing (DAS) Arrays for Seismic Monitoring of Offshore Carbon Storage

The current development of multiple Carbon Capture and Storage projects in the UK Continental Shelf, and Norwegian, Dutch and Danish North Sea, will be vital components of a secure, low carbon energy future for the region. The injection of many millions of tonnes of CO2 should also be accompanied by the implementation of a robust seismic monitoring system near large-scale injection facilities, due to the associated increase of the risk of inducing large seismic events during the injection. High resolution monitoring of microseismicity also provides important information about the geomechanical response of the reservoir and leakage risks such as caprock fracturing.

There is, however, a lack of seismic monitoring near offshore injection facilities due to the costly logistics challenges of operating in such settings. The implementation of Distributed Acoustic Sensing (DAS) technology has the potential to provide a cost-effective solution that can complement conventional methods to improve the robustness of seismic monitoring systems. In this study, we aim to evaluate the performance of offshore DAS arrays using a compilation of datasets which include areas within CCS licensees in the North Sea. We first examine for each DAS dataset the detectability of local and regional earthquakes using both conventional seismic processing methods and machine-learning methods (e.g. PhaseNet, N2N, DenoDAS), and then locate the detected events to quantify the location uncertainties associated with the geometry of offshore DAS arrays. Finally, we assess the capability of these networks to provide robust and reliable estimates of earthquake magnitudes.