Overcoming Urban Noise and Model Uncertainty

Abstract

Lack of data and urban noise pose significant challenges to monitoring anthropogenic seismicity in densely populated areas such as the Randstad region in the Netherlands. We deployed a temporary seismic array to monitor a geothermal doublet located at Kwintsheul, Netherlands. We implement innovative array processing, beamforming, and ML automatic-picking techniques to detect low-magnitude microseismic events that could be obscured by urban noise. Additionally, we propose a novel method to incorporate model uncertainties into hypocenter estimations based on the open-access subsurface information of the Netherlands. Contrary to previous studies, our analysis clearly shows that local low-magnitude seismicity does exist and highlights the value of denser seismic arrays and novel detection techniques for monitoring anthropogenic seismicity. The proposed hypocenter localization aids in avoiding under- or overestimation of location uncertainties, which is crucial for informed decision-making. This study advances seismic monitoring techniques in urban geothermal settings, providing critical data for informed decisionmaking and risk assessment of geothermal operations.