Distributed Acoustic Sensing (DAS) at the Plot to Basin Scale: Connecting Near-Surface Sensing and Seismology with a Common Observational Tool

Abstract:

With the increasing maturity of ambient noise imaging techniques, there has been growing interest in the near-surface community in leveraging permanent seismic sensors for tracking processes in the critical zone. A barrier preventing the utilization of permanent local or regional seismic networks for such purposes is the need for high spatial sampling and high frequency content to resolve structure at the decameter scale. Relevant signals are spatially aliased by sparse measurement networks, preventing full application to near-surface challenges in fields including hydrogeophysics. Distributed Acoustic Sensing (DAS) is a recently developed technique which utilizes fiber optic cables to measure dynamic strain at the meter scale and over domains of up to 30 km. The bandwidth of these measurements extends from the 100s of Hz down to mHz, allowing the same network to be utilized for both regional seismology as well as high-resolution imaging. This confluence presents an opportunity for both communities to develop joint instrumentation proposals as well as challenges in the design of appropriate data workflows which can satisfy these needs. We present data from several recent DAS studies illustrating this intersection between near-surface imaging and seismology including a study in the Sacramento Basin (Ajo-Franklin et al. 2019), a marine experiment in Monterey Bay (Lindsey et al. 2019), and an on-going experiment in the Imperial Valley. In these cases the measurement density of DAS allows simultaneous ambient noise imaging across a range of scales through utilization of different components of the noise spectrum from anthropogenic sources to microseism signals. The bandwidth of DAS allows simultaneous detection of earthquakes from the global to local scale as well as characterizing the spatial heterogeneity of noise sources. While the spatial density of DAS is a necessary pre-requisite for near-surface imaging, the same density can be leveraged for seismology by exploiting the array aspect of DAS for beam forming applications. We conclude by discussing the challenges of acquiring DAS data for near-surface sensing at the basin scale; high sensor densities yields an explosion in data volume, forcing careful consideration of data management strategies to effectively utilize this sensing tool.