Surface Wave Imaging Using Distributed Acoustic Sensing Deployed on Dark Fiber

Recently, distributed acoustic sensing (DAS) has been applied to shallow seismic structure imaging providing dense spatial sampling at a relatively low cost. DAS on a standard straight fiber-optic cable mostly records axial dynamic strain, which makes it difficult to separate the Rayleigh and Love wavefields. As a result, the mixed Rayleigh and Love wave signals cannot be used in the conventional surface-wave dispersion inversion method. Therefore, it is often ensured that the source and the cable are in the same line and only Rayleigh wave dispersion is used, which limits the constraints on structure and model resolution. We have inverted surface-wave dispersion spectra instead of dispersion curves. This inversion method can use mixed Rayleigh and Love waves recorded when the source and receiver array are not aligned. The multiple-channel records are transformed to the frequency domain, and a slant stack method is used to construct the dispersion spectra. The genetic algorithm method is used to obtain an optimal S-wave velocity model that minimizes the difference between theoretical and observed dispersion spectra. A series of synthetic tests are conducted to validate our method. The results suggest that our method not only improves the flexibility of the acquisition system design, but the Love wave data also provide additional constraints on the structure. Our method is applied to the active source and ambient noise data sets acquired at a geothermal site and provides consistent results for different data sets and acquisition geometries. The sensitivity of the dispersion spectra to layer thickness, density, and P-wave velocity is also discussed. With our method, the amount of usable data can be increased, helping deliver better subsurface images.

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Low-frequency Ambient Distributed Acoustic Sensing (DAS): Case Study from Perth, Australia

Geophysical Journal International ◽

10.1093/gji/ggab111 ◽

2021 ◽

Author(s):

Jeffrey Shragge ◽

Jihyun Yang ◽

Nader Issa ◽

Michael Roelens ◽

Michael Dentith ◽

...

Keyword(s):

Surface Wave ◽

Optical Fiber ◽

Low Frequency ◽

Wave Analysis ◽

Near Surface ◽

Acoustic Sensing ◽

Geotechnical Investigations ◽

Wide Range ◽

Distributed Acoustic Sensing

Summary Ambient wavefield data acquired on existing (so-called “dark fiber”) optical fiber networks using distributed acoustic sensing (DAS) interrogators allow users to conduct a wide range of subsurface imaging and inversion experiments. In particular, recorded low-frequency (<2 Hz) surface-wave information holds the promise of providing constraints on the shear-wave velocity (VS) to depths exceeding 0.5 km. However, surface-wave analysis can be made challenging by a number of acquisition factors that affect the amplitudes of measured DAS waveforms. To illustrate these sensitivity challenges, we present a low-frequency ambient wavefield investigation using a DAS dataset acquired on a crooked-line optical fiber array deployed in suburban Perth, Western Australia. We record storm-induced microseism energy generated at the nearby Indian Ocean shelf break and/or coastline in a low-frequency band (0.04 − 1.80 Hz) and generate high-quality virtual shot gathers (VSGs) through cross-correlation and cross-coherence interferometric analyses. The resulting VSG volumes clearly exhibit surface-wave energy, though with significant along-line amplitude variations that are due to the combined effects of ambient source directivity, crooked-line acquisition geometry, and the applied gauge length, fiber coupling, among other factors. We transform the observed VSGs into dispersion images using two different methods: phase shift and high-resolution linear Radon transform. These dispersion images are then used to estimate 1-D near-surface VS models using multi-channel analysis of surface-waves (MASW), which involves picking and inverting the estimated Rayleigh-wave dispersion curves using the particle-swarm optimization global optimization algorithm. The MASW inversion results, combined with nearby deep borehole information and 2-D elastic finite-difference modeling, show that low-frequency ambient DAS data constrain the VS model, including a low-velocity channel, to at least 0.5 km depth. Thus, this case study illustrates the potential of using DAS technology as a tool for undertaking large-scale surface-wave analysis in urban geophysical and geotechnical investigations to depths exceeding 0.5 km.

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Measurement of Surface-Wave Phase-Velocity Dispersion on Mixed Inertial Seismometer – Distributed Acoustic Sensing Seismic Noise Cross-Correlations

Bulletin of the Seismological Society of America ◽

10.1785/0120210028 ◽

2021 ◽

Author(s):

Avinash Nayak ◽

Jonathan Ajo-Franklin ◽

Keyword(s):

Surface Wave ◽

Phase Velocity ◽

Rayleigh Waves ◽

Cross Correlation ◽

Axial Strain ◽

Phase Velocity Dispersion ◽

Wave Phase Velocity ◽

Wave Imaging ◽

Cross Correlations ◽

Distributed Acoustic Sensing

ABSTRACT The application of ambient seismic noise cross-correlation to distributed acoustic sensing (DAS) data recorded by subsurface fiber-optic cables has revolutionized our ability to obtain high-resolution seismic images of the shallow subsurface. However, passive surface-wave imaging using DAS arrays is often restricted to Rayleigh-wave imaging and 2D imaging along straight segments of DAS arrays due to the intrinsic sensitivity of DAS being limited to axial strain along the cable for the most common type of fiber. We develop the concept of estimating empirical surface waves from mixed-sensor cross-correlation of velocity noise recorded by three-component seismometers and strain-rate noise recorded by DAS arrays. Using conceptual arguments and synthetic tests, we demonstrate that these cross-correlations converge to empirical surface-wave axial strain response at the DAS arrays for virtual single step forces applied at the seismometers. Rotating the three orthogonal components of the seismometer to a tangential–radial–vertical reference frame with respect to each DAS channel permits separate analysis of Rayleigh waves and Love waves for a medium that is sufficiently close to 1D and isotropic. We also develop and validate expressions that facilitate the measurement of surface-wave phase velocity on these noise cross-correlations at far-field distances using frequency–time analysis. These expressions can also be used for DAS surface-wave records of active sources at local distances. We demonstrate the recovery of both Rayleigh waves and Love waves in noise cross-correlations derived from a dark fiber DAS array in the Sacramento basin, northern California, and nearby permanent seismic stations at frequencies ∼0.1–0.2 Hz, up to distances of ∼80 km. The phase-velocity dispersion measured on these noise cross-correlations are consistent with those measured on traditional noise cross-correlations for seismometer pairs. Our results extend the application of DAS to 3D ambient noise Rayleigh-wave and Love-wave tomography using seismometers surrounding a DAS array.

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