Surface wave imaging of the weakly extended Malawi Rift from ambient-noise and teleseismic Rayleigh waves from onshore and lake-bottom seismometers

Abundant noise sources in urban area has been widely utilized for subsurface investigations based on the seiemic interferometry. Reliable dispersion extraction between two seismic stations is an essential basis of surface wave imaging. Noise source directivity has become an inescapable obstacle and a main concern for passive seismic surveys: it basically breaks the physics of Green&#8217;s function retrieval in travel-time tomography; Moreover, the azimuthal effect of ambient noise sources would inherently cause different levels of early arrival on cross-correlation functions, so that the apparent velocity of surface wave could be overestimated in multichannel slant stackings.&#160;Instead of the conventional frequency-time analysis, which aims to extract the apparent dispersions of phase/group velocity between seismic stations, we proposed a method to jointly invert noise source distributions and the corresponding unbiased surface wave velocities based on the theoretical framework of full waveform ambient noise inversion. Waveform itself could intrinsically contains the features of travel-time, energy and asymmetry of ambient noise cross correlation functions (NCF). And they could in return map the resulted NCF into the noise source distributions and velocity structures. The L2 norm of cross-correlating waveform misfits was taken as the objective function to conduct gradient based inversion (i.e. the L-BFGS algorithm). We parametrized the noise source distributions as a temporally ensemble averaged model, which was discretized as a spatially plane grid of normalized source strength. The surface wave velocity model was approximated as the straight-ray interstation velocity. The two kinds of variants were decoupled in waveform misfit function by their corresponding partial derivatives to iteratively update the model space.&#160;The effectiveness of source-velocity joint imaging using above full waveform inversion work flow was qualified by both the synthetic test and the applied research in Hangzhou urban area. The inverted noise source model was comparable with the urban traffic- and construction- noise distributions. And the truthful surface wave velocities were achieved considering the constraint of noise source distributions, they were also prior constrained and later verified by local borehole datasets.

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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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Imaging the subsurface using induced seismicity and ambient noise: 3-D tomographic Monte Carlo joint inversion of earthquake body wave traveltimes and surface wave dispersion

Geophysical Journal International ◽

10.1093/gji/ggaa230 ◽

2020 ◽

Vol 222 (3) ◽

pp. 1639-1655

Author(s):

Xin Zhang ◽

Corinna Roy ◽

Andrew Curtis ◽

Andy Nowacki ◽

Brian Baptie

Keyword(s):

Surface Wave ◽

Ambient Noise ◽

Velocity Structure ◽

Joint Inversion ◽

Body Wave ◽

Source Parameters ◽

Wave Dispersion ◽

Inversion Method ◽

Surface Wave Dispersion ◽

Wave Data

SUMMARY Seismic body wave traveltime tomography and surface wave dispersion tomography have been used widely to characterize earthquakes and to study the subsurface structure of the Earth. Since these types of problem are often significantly non-linear and have non-unique solutions, Markov chain Monte Carlo methods have been used to find probabilistic solutions. Body and surface wave data are usually inverted separately to produce independent velocity models. However, body wave tomography is generally sensitive to structure around the subvolume in which earthquakes occur and produces limited resolution in the shallower Earth, whereas surface wave tomography is often sensitive to shallower structure. To better estimate subsurface properties, we therefore jointly invert for the seismic velocity structure and earthquake locations using body and surface wave data simultaneously. We apply the new joint inversion method to a mining site in the United Kingdom at which induced seismicity occurred and was recorded on a small local network of stations, and where ambient noise recordings are available from the same stations. The ambient noise is processed to obtain inter-receiver surface wave dispersion measurements which are inverted jointly with body wave arrival times from local earthquakes. The results show that by using both types of data, the earthquake source parameters and the velocity structure can be better constrained than in independent inversions. To further understand and interpret the results, we conduct synthetic tests to compare the results from body wave inversion and joint inversion. The results show that trade-offs between source parameters and velocities appear to bias results if only body wave data are used, but this issue is largely resolved by using the joint inversion method. Thus the use of ambient seismic noise and our fully non-linear inversion provides a valuable, improved method to image the subsurface velocity and seismicity.

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