Seismic Noise Reduction as a Function of Depth Recorded by a Vertical Array Installed in a 285-m-Deep Borehole at a Gas Storage Field in Northern Italy

The background seismic noise can be generated by different sources such as, ocean waves (microseisms), atmospheric disturbances (strong wind and storms), and anthropogenic activities, temperature changes and magnetic field variations. Such disturbances are char-acterized by specific frequency bands, time occurrence (diurnal and seasonal variation), and site location (close to populated areas or to the coasts). Reducing the pernicious effect of these noise sources is one of the main challenges that seismologists and engi-neers need to face when designing seismic monitoring networks and, more specifically when selecting the hosting site of a seismic station. A solution to partially attenuate the seismic noise effect is achieved by deploying seismic stations in boreholes. A general law estimating the sufficient depth to gain to detect even low seismic events, highly masked by background noise, is fundamental for defining the capability of microseismic network. Here, we aim to characterize the seismic noise level at S. Potito-Cotignola in the Po Valley, Italy, from January 2019 to December 2021 recorded by a broadband seismic station at surface and a vertical array composed by six short-period three-component seismometers installed at depth ranging between 35 and 285 m in borehole. We compute the amplitude noise reduction as a function of depth for different frequencies and we evaluate the depth dependency of the signal to noise ratio for 18 seismic events, with different mag-nitude (from -0.1 to 2.9) and hypocentral distances (from 12.9 to 37.2 km). Results show that (1) the dependence of noise level with depth follows a logarithmic empirical trend and (2) most of the selected seismic events show that signal to noise ratio increases with depth. The empirical relationships we estimated can be used to help the design of micro -seismic monitoring networks in similar geological settings.