Benjumea, B., Gaite, B., Schimmel, M., Bohoyo, F., Spica, Z. J., Mancilla, F. D. L., Li, Y., Almendros, J., & Morales, J. (2024). Subsurface Imaging in Urban Areas With Ambient Noise Using DAS and Seismometer Data Sets: Granada, Spain. Journal of Geophysical Research: Solid Earth, 129(11), e2024JB029820. https://doi.org/10.1029/2024JB029820

Abstract

Distributed acoustic sensing (DAS) is an innovative technology with great potential for acquiring seismic data sets in urban areas. In this work, we check the suitability of a DAS data set acquired in Granada (Spain) for retrieving subsurface reflectivity from ambient noise. The fiber-optic is a pre-existing underground telecommunication cable that crosses the city from Northwest to Southeast. We use a 10 hr recording of strain rate from a 2020 experiment to obtain seismic reflections using the autocorrelation method. We compare the DAS results with reflections obtained from seismic ambient noise recorded in nine seismometers deployed close to the fiber-cable for 7 days in November 2022. The novel approach proposed in this study for the identification of the reflections is to use autocorrelations after bandpass filtering for specific central frequencies and to check the stability of the signals over a broad frequency band. Microtremor Horizontal to Vertical Spectral Ratio (MHVSR) measurements at a total of 14 stations, five of them outside the city, help to constrain the reflection interpretation. These include one station at the borehole that reaches the basement in the Granada Basin crossing all the Cenozoic units. We use the legacy sonic log to obtain a relationship between frequencies of MHVSR peaks and depth. Autocorrelation and MHVSR methods give consistent results delineating bedrock depth deeper than 1,000 m in Granada. These results confirm that DAS can provide valuable subsurface information in urban areas.