Seismic Imaging from scattered waves using Distributed Acoustic Sensing offshore Central Chile

Distributed Acoustic Sensing (DAS) is becoming a standard solution for ocean-bottom seismological acquisition by providing a dense and long-distance measurement of ground deformation along offshore submarine fiber-optic cables. In the context of an offshore deployment in Central Chile, fiber-optic cables provide real-time seismic data dominated by scattered and converted phases. In a previous work, we have developed a methodology to determine both the velocity and thickness of the shallow sedimentary layer under the fiber using surface waves and split P-waves. Our current objective is to enhance the crustal imaging by identifying fault zones characterized by strong wavefront scattering and sharp lateral velocity contrasts, and sedimentary basins geometry at sub-kilometer scales in the same area, using scattered surface waves.

We focus on seismic events recorded along a 150-km-long fiber in Central Chile. After partitioning the wavefield to separate direct waves from surface waves, we compute local backprojections of the scattered wavefield. By analyzing multiple seismic events across different frequencies, we investigate variations in wave propagation at multiple scales. The resulting energy profiles reveal spatially resolved fault zone structures and sharp lateral contrasts that align with topographic and structural features. Additionally, using standard seismic noise processing procedures, we compute time-domain cross-correlation functions, autocorrelations, and spectral densities. These analyses provide further insights into the behavior of surface waves near reflector features. For instance, we identify lateral discontinuities associated with basin edges by measuring their frequency-dependent resonance.

Finally, to assess the seismogenic potential of the imaged structures, we will compare the geographical distribution and extent of the detected structures with the shallow seismicity automatically detected in the area using DAS data.