Understanding Dark Fibre DAS Ambient Seismic Noise recordings in Urban Areas: Implications for Subsurface Imaging in Istanbul

Urban environments currently host more than 55% of the global population. However, the subsurface of such environments is not well characterized. Conventional geophysical surveys pose logistical challenges, such as restricted access and limitations on the use of active seismic sources, which impede such surveys to be performed. To overcome these challenges, Distributed Acoustic Sensing (DAS) can be deployed on existing, unused telecommunication fibre optic cables (dark fibres) and repurpose them as dense seismic arrays. In this way, the ambient seismic wavefield can be continuously recorded for high-resolution, passive subsurface imaging. However, the seismic noise field present in urban environments is complex, and mostly dominated by anthropogenic activity (i.e., trains, cars…), resulting in transient and moving seismic sources. Besides, dark fibres tend to have complicated layouts. A thorough understanding of the urban seismic noise field recorded by dark fibre DAS arrays is needed to understand the retrieved energy and its potential for seismic imaging.

In this work, we investigate the interaction between diverse noise sources, complex fibre geometries and DAS directional sensitivity, and its impact on the application of ambient noise interferometry for imaging in complex urban environments. Our study area is located in the megacity of Istanbul (Türkiye), a highly densely populated urban area sitting in a region of high earthquake risk. The subsurface structure beneath Istanbul is poorly known, with very limited information available regarding subsurface material properties and faults directly underneath the city. Since May 2024, we have been continuously and simultaneously recording passive DAS data along two dark fibres located on the Eastern side of Istanbul; one crossing the densely populated district of Kartal and another one connecting the coastal section of Kartal with the Princess Islands archipelago, directly offshore.

We start by analysing the ambient noise field recorded along fibre segments with different orientations and at diverse time periods; trying to isolate low-frequency seismic energy generated by natural sources. Combining measurements along both fibres, we apply beamforming approaches to understand the distribution of noise sources with respect to our array, and explore optimal channel-pair configurations to retrieve Rayleigh and Love waves, by taking into account the directional sensitivity of the DAS measurement. Ultimately, our goal is to develop a methodological framework for obtaining a reliable subsurface velocity model using seismic ambient noise in urban areas.