Distributed Acoustic Sensing Using Dark Fiber for Array Detection of Regional Earthquakes

Abstract

Abstract The intrinsic array nature of distributed acoustic sensing (DAS) makes it suitable for applying beamforming techniques commonly used in traditional seismometer arrays for enhancing weak and coherent seismic phases from distant seismic events. We test the capacity of a dark-fiber DAS array in the Sacramento basin, northern California, to detect small earthquakes at The Geysers geothermal field, at a distance of ∼100  km from the DAS array, using beamforming. We use a slowness range appropriate for ∼0.5–1.0  Hz surface waves that are well recorded by the DAS array. To take advantage of the large aperture, we divide the ∼20  km DAS cable into eight subarrays of aperture ∼1.5–2.0  km each, and apply beamforming independently to each subarray using phase-weighted stacking. The presence of subarrays of different orientations provides some sensitivity to back azimuth. We apply a short-term average/long-term average detector to the beam at each subarray. Simultaneous detections over multiple subarrays, evaluated using a voting scheme, are inferred to be caused by the same earthquake, whereas false detections caused by anthropogenic noise are expected to be localized to one or two subarrays. Analyzing 45 days of continuous DAS data, we were able to detect all earthquakes with M≥2.4, while missing most of the smaller magnitude earthquakes, with no false detections due to seismic noise. In comparison, a single broadband seismometer co-located with the DAS array was unable to detect any earthquake of M<2.4, many of which were detected successfully by the DAS array. The seismometer also experienced a large number of false detections caused by spatially localized noise. We demonstrate that DAS has significant potential for local and regional detection of small seismic events using beamforming. The ubiquitous presence of dark fiber provides opportunities to extend remote earthquake monitoring to sparsely instrumented and urban areas.