Advancing Earthquake Rupture Imaging through Ocean Bottom Distributed Acoustic Sensing Data

Utilizing Seafloor Fiber Optic Cables with Distributed Acoustic Sensing (DAS) provides a cost-effective alternative to traditional cabled ocean bottom seismic networks by offering seismic data with high-density and extensive coverage near seismic sources. This innovative method holds great potential for advancing offshore monitoring systems aimed at hazard mitigation and enhancing our understanding of earthquake mechanics. In this study, we present a methodological approach for back-projection imaging of earthquake ruptures using DAS data from the ocean floor off the coast of Chile. Our approach leverages the unique characteristics of DAS data to significantly improve the resolution and precision in estimating the source parameters of local earthquakes.

Our methodology encompasses several steps to optimize back-projection performance. We employ spatial integration to convert DAS strains into displacements, mitigating the adverse effects of wave scattering on waveform coherence. We enhance travel time accuracy through shallow-sediment time corrections and utilize array processing on overlapping cable segments (sub-arrays) to determine apparent slowness. The collective information from all sub-arrays is then used to localize earthquakes employing a 1D local velocity model.

Through extensive synthetic testing with the 120-km-long cable configuration off Chile's coast, we identified a "high-precision, high-resolution source region," less affected by velocity structure uncertainties. This region spans approximately 80 km laterally from the cable and reaches depths of up to 15 km, likely due to optimal signal focusing from various angles, extendable with increased cable length. Our method applied to data from around 50 local earthquakes with magnitudes ranging from 1.5 to 3 consistently yields sharp back-projection images with high spatial accuracy, within 1 to 4 km, for earthquakes within this defined region, comparable to seismic catalog location uncertainties.

Our approach's real potential lies in its capacity to image the rupture process of larger earthquakes. Applying our method to synthetic waveforms of a magnitude 7 earthquake constructed from multiple empirical Green's functions, we demonstrate that strong coda waves do not hinder the precise detection and localization of subsequent sub-sources, provided travel time calibration is applied. The rupture speeds and locations of sub-sources are accurately recovered, even for concurrent multiple sources. Ongoing enhancements to travel time calibration aim to further increase location accuracy and resolution, including waveform alignment with static calibration, 3D velocity model travel time tables, and slowness bias measurements and calibrations for each source-subarray pair. Together, these improvements will boost the resolution and accuracy of our method, alongside more sophisticated back-propagation methods for individual arrays. Our work shows promise for earthquake and tsunami early warning development, contingent upon effectively addressing the amplitude saturation issue of DAS data.