We analyze active and passive seismic data recorded by the Stanford distributed acoustic sensing array (SDASA) located in conduits under the Stanford University campus. For the active data we used low-energy sources (betsy gun and sledge hammer) and recorded data using both the DAS array and 98 three-component nodes deployed along a 2D line. The joint analysis of shot profiles extracted from the two data sets shows that some surface waves and refracted events are consistently recorded by the DAS array. In areas where geophone coupling was suboptimal because of surface obstructions, DAS recordings are more coherent. In contrast, surface waves are more reliably recorded by the geophones than the DAS array. Because of the noisy environment and weak sources, neither data set shows clear reflections. We demonstrate the repeatability of DAS recordings of local earthquakes by comparing two weak events (magnitude 0.95 and 1.34) with epicenters 100 m apart that occurred only one minute from each other. Analyzing another local, and slightly stronger, earthquake (magnitude 2.0) we show how the kinematics of both the P-arrival and S-arrival can be measured from the DAS data. Interferometric analysis of passive data shows that reliable virtual-source responses can be extracted from the DAS data. We observe Rayleigh waves when correlating aligned receivers, and Love waves when correlating receivers belonging to segments of the array parallel to each other. Dispersion analysis of the virtual sources shows the expected decrease in surface-wave velocity with increasing frequency.
Martin ER, Castillo CM, Cole S, Sawasdee PS, Yuan S, et al. (2017) Seismic monitoring leveraging existing telecom infrastructure at the SDASA: Active, passive, and ambient-noise analysis. The Leading Edge 36: 1025–1031. Available: http://dx.doi.org/10.1190/tle36121025.1.
This research was financially supported by affiliates of the Stanford Exploration Project. The IU was loaned to us by OptaSense Inc. E. Martin additionally received financial support through the Department of Energy Computational Science Graduate Fellowship under grant DE-FG02-97ER25308 and a Schlumberger Innovation Fellowship. This experiment is also made possible through the efforts of the Stanford IT fiber team and SEEES IT. Computing resources were provided through the Stanford Center for Computational Earth and Environmental Sciences. We thank Fan-Chi Lin and the University of Utah Seismograph Station for the use of their nodes, some of which were purchased under King Abdullah University of Science and Technology award OCRF-2014-CRG3-2300 and USGS Earthquake Hazards Program grant G17AP00003. We also thank Subsea Systems, California State University-Long Beach, and the Stanford Crustal Geophysics Group for equipment loans. We thank S. Levin for advice and field work assistance, J. Chang for ambient-noise processing advice, S. Klemperer for active-survey advice, and E. Williams and C. Laing for field work setting up and calibrating the array, as well as many Stanford-affiliated volunteers for field work during the active survey. We thank our colleagues at Lawrence Berkeley Lab and the University of California-Berkeley, J. Ajo-Franklin and N. Lindsey, for helpful discussions about their early tests using existing telecomm fiber for DAS.