Surface Wave Imaging Using Distributed Acoustic Sensing Deployed on Dark Fiber

Abstract

Several recent studies have demonstrated that “distributed acoustic sensing” (DAS) can utilize existing subsurface telecommunication fiber (i.e., dark fiber) for high-quality seismic measurements. Researchers to date have shown that this sensing combination, coupled with ambient noise interferometry techniques, can effectively image the shallow subsurface (<30 m) using vehicle and infrastructure noise ( f = 8–30 Hz). We present a long-offset surface wave inversion study targeting deeper (≈500 m) structure using DAS and dark fiber. This study utilizes a previously acquired data set collected on a 23 km fiber section between West Sacramento and Woodland, California, part of the Energy Sciences Network (ESnet) of the U.S. Department of Energy. By targeting noise generated by a colinear rail line, broadband and rich in low frequencies (down to f = 1 Hz), and long array offsets, we generate high-quality interferometric gathers suitable for inversion. Subsequent surface wave inversions using a multimode Monte Carlo sampling algorithm are consistent with geology and available confirmatory data sets derived from colocated sonic logs. The relatively sparse confirmatory data demonstrate, by comparison, the utility of the high spatial sampling provided by DAS. These results open the door to larger regional DAS studies targeting deeper targets, but with resolutions higher than those afforded by the use of persistent low-frequency ( f < 1 Hz) ocean microseism-related noise.