Ambient Seismic Noise: From Characterization to Simulation

Ambient seismic noise, traditionally viewed as undesired signal in seismic records, has increasingly gained importance as a source of information for site characterization and seismic monitoring. With the growing demand for exploitation of alternative energy resources (e.g. geothermal projects) in urban and suburban environments, understanding the spatial distribution and seismic noise levels - generated by both natural sources and anthropogenic sources - is critical for subsurface characterization as well as for optimizing microseismic monitoring networks.

In this work, we analyzed eight days of continuous recordings from a temporary seismic monitoring network in Switzerland. The main noise sources in the study area were identified through the analysis of satellite maps and their corresponding spectral characteristics were extracted from the passive seismic records. Seismic noise from the most powerful sources (trains) was used to derive the frequency-dependent attenuation coefficient (α). Moreover, seismic interferometry was applied to a subset of stations to estimate Rayleigh waves dispersion. These two pieces of information were combined to estimate the seismic quality factor (Q) of the subsurface.

We will highlight how the noise spectra database we built is a step toward optimizing several seismological applications. Specifically, it will reduce interpolation-related uncertainty in probabilistic power spectral density noise maps and will provide a first-order approximation of expected noise levels acting as a predictive tool in unmonitored areas.

 

This study was developed in the frame of “The Geosciences for Sustainable Development” project (Budget Ministero dell’Università e della Ricerca–Dipartimenti di Eccellenza 2023–2027 C93C23002690001).