scholarly journals Surface-wave analysis for building near-surface velocity models — Established approaches and new perspectives

Geophysics ◽  
2010 ◽  
Vol 75 (5) ◽  
pp. 75A83-75A102 ◽  
Author(s):  
Laura Valentina Socco ◽  
Sebastiano Foti ◽  
Daniele Boiero
Keyword(s):  
Surface Wave ◽  
Rapid Evolution ◽  
Surface Velocity ◽  
Wave Analysis ◽  
S Wave ◽  
Near Surface ◽  
Scientific Debate ◽  
Velocity Models ◽  
Surface Wave Method ◽  
Lateral Variations

Today, surface-wave analysis is widely adopted for building near-surface S-wave velocity models. The surface-wave method is under continuous and rapid evolution, also thanks to the lively scientific debate among different disciplines, and interest in the technique has increased significantly during the last decade. A comprehensive review of the literature in the main scientific journals provides historical perspective, methodological issues, applications, and most-promising recent approaches. Higher modes in the inversion and retrieval of lateral variations are dealt with in great detail, and the current scientific debate on these topics is reported. A best-practices guideline is also outlined.

High-frequency ambient noise surface wave tomography at the Marathon PGE-Cu deposit (Ontario, Canada)

2021 ◽  
Author(s):  
Daniela Teodor ◽  
Charles Beard ◽  
Laura Alejandra Pinzon-Rincon ◽  
Aurélien Mordret ◽  
François Lavoué ◽  
...  
Keyword(s):  
Surface Wave ◽  
High Frequency ◽  
Ambient Noise ◽  
Dispersion Curves ◽  
Wave Analysis ◽  
S Wave ◽  
Noise Sources ◽  
Velocity Models ◽  
Wave Tomography ◽  
Average Dispersion

<p>Ambient noise surface wave tomography (ANSWT) is an environmentally friendly and cost-effective technique for subsurface imaging. In this study, we used natural (low-frequency) and anthropogenic (high-frequency) noise sources to map the velocity structure of the Marathon Cu-PGE deposit (Ontario, Canada) to a depth of 1 km. The Marathon deposit is a circular (ø = 25 km) alkaline intrusion comprising gabbros at the rim and an overlying series of syenites in the centre. Cu-PGE mineralisation is hosted by gabbros close to the inward-dipping footwall of the intrusion. The country rocks are Archaean volcanic breccias that are seismically slower than the gabbros, and similar in velocity to the syenites. We used ANSWT to image the footwall contact that controls the location of the mineralisation.</p><p>An array of 1024 vertical-component receivers were deployed for 30 days to record ambient noise required for surface wave analysis. Two overlapping grids were used: a 200 m x 6040 m dense array with node spacing of 50 m, and a 2500 m x 4000 m sparse array with node spacing of 150 m.  The signal was down-sampled to 50 Hz, divided into segments of 30 minutes, cross-correlated and stacked. Surface wave analysis was conducted over the dense array and the sparse array data. We considered the fundamental mode of Rayleigh wave propagation for our frequency-wavenumber (F-K) analysis and focused on the phase velocity variation in the high-frequency ambient noise signal (up to 22 Hz). We reconstructed the shallow structure with progressively increased resolution using surface wave dispersion curves extracted from receiver arrays divided into segments of variable lengths. Several average dispersion curves were computed from individual dispersion curves belonging to different seismic lines. Each average dispersion curve was inverted to obtain S-wave velocity models using an McMC transdimensional Bayesian approach.</p><p>The tomographic images reveal a shallow high-velocity anomaly, which we interpret as being related to the gabbro intrusion that hosts the mineralization. The large-wavelength structures in the S-wave velocity models are relatively consistent with the geological structures inferred from surface mapping and drill core data. These results show that the ANSWT, focused on the high-frequency signal provided by anthropogenic noise sources, is an efficient technique for imaging “shallow" (1 km depth) geological structures in a mineral exploration context. </p>

Computing near-surface velocity models for S-wave static corrections using raypath interferometry

Geophysics ◽  
2018 ◽  
Vol 83 (3) ◽  
pp. U23-U34
Author(s):  
Raul Cova ◽  
David Henley ◽  
Kristopher A. Innanen
Keyword(s):  
Wave Velocity ◽  
Velocity Model ◽  
P Wave ◽  
Surface Velocity ◽  
S Wave ◽  
Converted Wave ◽  
Near Surface ◽  
Velocity Models ◽  
Consistent Solution ◽  
Static Corrections

A near-surface velocity model is one of the typical products generated when computing static corrections, particularly in the processing of PP data. Critically refracted waves are the input usually needed for this process. In addition, for the converted PS mode, S-wave near-surface corrections must be applied at the receiver locations. In this case, however, critically refracted S-waves are difficult to identify when using P-wave energy sources. We use the [Formula: see text]-[Formula: see text] representation of the converted-wave data to capture the intercept-time differences between receiver locations. These [Formula: see text]-differences are then used in the inversion of a near-surface S-wave velocity model. Our processing workflow provides not only a set of raypath-dependent S-wave static corrections, but also a velocity model that is based on those corrections. Our computed near-surface S-wave velocity model can be used for building migration velocity models or to initialize elastic full-waveform inversions. Our tests on synthetic and field data provided superior results to those obtained by using a surface-consistent solution.

Surface wave tomography to retrieve near surface velocity models

2014 ◽  
Author(s):  
Laura Valentina Socco* ◽  
Daniele Boiero ◽  
Paolo Bergamo ◽  
Flora Garofalo ◽  
Huajian Yao ◽  
...  
Keyword(s):  
Surface Wave ◽  
Surface Velocity ◽  
Surface Wave Tomography ◽  
Near Surface ◽  
Velocity Models ◽  
Wave Tomography

Tunnel detection at Yuma Proving Ground, Arizona, USA — Part 1: 2D full-waveform inversion experiment

Geophysics ◽  
2019 ◽  
Vol 84 (1) ◽  
pp. B95-B105 ◽  
Author(s):  
Yao Wang ◽  
Richard D. Miller ◽  
Shelby L. Peterie ◽  
Steven D. Sloan ◽  
Mark L. Moran ◽  
...  
Keyword(s):  
Surface Wave ◽  
Waveform Inversion ◽  
Velocity Profiles ◽  
Infinite Length ◽  
Full Waveform Inversion ◽  
S Wave ◽  
Near Surface ◽  
Tunnel Detection ◽  
Full Waveform ◽  
Wave Methods

We have applied time domain 2D full-waveform inversion (FWI) to detect a known 10 m deep wood-framed tunnel at Yuma Proving Ground, Arizona. The acquired seismic data consist of a series of 2D survey lines that are perpendicular to the long axis of the tunnel. With the use of an initial model estimated from surface wave methods, a void-detection-oriented FWI workflow was applied. A straightforward [Formula: see text] quotient masking method was used to reduce the inversion artifacts and improve confidence in identifying anomalies that possess a high [Formula: see text] ratio. Using near-surface FWI, [Formula: see text] and [Formula: see text] velocity profiles were obtained with void anomalies that are easily interpreted. The inverted velocity profiles depict the tunnel as a low-velocity anomaly at the correct location and depth. A comparison of the observed and simulated waveforms demonstrates the reliability of inverted models. Because the known tunnel has a uniform shape and for our purposes an infinite length, we apply 1D interpolation to the inverted [Formula: see text] profiles to generate a pseudo 3D (2.5D) volume. Based on this research, we conclude the following: (1) FWI is effective in near-surface tunnel detection when high resolution is necessary. (2) Surface-wave methods can provide accurate initial S-wave velocity [Formula: see text] models for near-surface 2D FWI.

P- and S-wave velocity models from surface wave dispersion curves data transform

2017 ◽  
Author(s):  
Valentina Socco ◽  
Farbod Khosro Anjom ◽  
Cesare Comina ◽  
Daniela Teodor
Keyword(s):  
Surface Wave ◽  
Wave Velocity ◽  
Wave Dispersion ◽  
Dispersion Curves ◽  
S Wave ◽  
Surface Wave Dispersion ◽  
Velocity Models

Ground roll: A potential tool for constraining shallow shear‐wave structure

Geophysics ◽  
1993 ◽  
Vol 58 (5) ◽  
pp. 713-719 ◽  
Author(s):  
Ghassan I. Al‐Eqabi ◽  
Robert B. Herrmann
Keyword(s):  
Surface Wave ◽  
Phase Velocity ◽  
Wave Velocity ◽  
Wave Structure ◽  
S Wave ◽  
Data Set ◽  
Velocity Inversion ◽  
Ground Roll ◽  
Lateral Variations ◽  
Wave Arrival

The objective of this study is to demonstrate that a laterally varying shallow S‐wave structure, derived from the dispersion of the ground roll, can explain observed lateral variations in the direct S‐wave arrival. The data set consists of multichannel seismic refraction data from a USGS-GSC survey in the state of Maine and the province of Quebec. These data exhibit significant lateral changes in the moveout of the ground‐roll as well as the S‐wave first arrivals. A sequence of surface‐wave processing steps are used to obtain a final laterally varying S‐wave velocity model. These steps include visual examination of the data, stacking, waveform inversion of selected traces, phase velocity adjustment by crosscorrelation, and phase velocity inversion. These models are used to predict the S‐wave first arrivals by using two‐dimensional (2D) ray tracing techniques. Observed and calculated S‐wave arrivals match well over 30 km long data paths, where lateral variations in the S‐wave velocity in the upper 1–2 km are as much as ±8 percent. The modeled correlation between the lateral variations in the ground‐roll and S‐wave arrival demonstrates that a laterally varying structure can be constrained by using surface‐wave data. The application of this technique to data from shorter spreads and shallower depths is discussed.

3D elastic full-waveform inversion of surface waves in the presence of irregular topography using an envelope-based misfit function

Geophysics ◽  
2018 ◽  
Vol 83 (1) ◽  
pp. R1-R11 ◽  
Author(s):  
Dmitry Borisov ◽  
Ryan Modrak ◽  
Fuchun Gao ◽  
Jeroen Tromp
Keyword(s):  
Surface Wave ◽  
Objective Function ◽  
Surface Waves ◽  
Large Scale ◽  
Body Wave ◽  
Waveform Inversion ◽  
Full Waveform Inversion ◽  
S Wave ◽  
Near Surface ◽  
Full Waveform

Full-waveform inversion (FWI) is a powerful method for estimating the earth’s material properties. We demonstrate that surface-wave-driven FWI is well-suited to recovering near-surface structures and effective at providing S-wave speed starting models for use in conventional body-wave FWI. Using a synthetic example based on the SEG Advanced Modeling phase II foothills model, we started with an envelope-based objective function to invert for shallow large-scale heterogeneities. Then we used a waveform-difference objective function to obtain a higher-resolution model. To accurately model surface waves in the presence of complex tomography, we used a spectral-element wave-propagation solver. Envelope misfit functions are found to be effective at minimizing cycle-skipping issues in surface-wave inversions, and surface waves themselves are found to be useful for constraining complex near-surface features.

Shallow velocity structure and poisson's ratio at the Tarzana, California, strong-motion accelerometer site

1996 ◽  
Vol 86 (6) ◽  
pp. 1704-1713 ◽  
Author(s):  
R. D. Catchings ◽  
W. H. K. Lee
Keyword(s):  
Urban Areas ◽  
Velocity Structure ◽  
Strong Motion ◽  
P Wave ◽  
S Wave ◽  
Near Surface ◽  
Velocity Models ◽  
Wave Velocities ◽  
Poisson's Ratios ◽  
Poisson’S Ratios

Abstract The 17 January 1994, Northridge, California, earthquake produced strong ground shaking at the Cedar Hills Nursery (referred to here as the Tarzana site) within the city of Tarzana, California, approximately 6 km from the epicenter of the mainshock. Although the Tarzana site is on a hill and is a rock site, accelerations of approximately 1.78 g horizontally and 1.2 g vertically at the Tarzana site are among the highest ever instrumentally recorded for an earthquake. To investigate possible site effects at the Tarzana site, we used explosive-source seismic refraction data to determine the shallow (<70 m) P-and S-wave velocity structure. Our seismic velocity models for the Tarzana site indicate that the local velocity structure may have contributed significantly to the observed shaking. P-wave velocities range from 0.9 to 1.65 km/sec, and S-wave velocities range from 0.20 and 0.6 km/sec for the upper 70 m. We also found evidence for a local S-wave low-velocity zone (LVZ) beneath the top of the hill. The LVZ underlies a CDMG strong-motion recording site at depths between 25 and 60 m below ground surface (BGS). Our velocity model is consistent with the near-surface (<30 m) P- and S-wave velocities and Poisson's ratios measured in a nearby (<30 m) borehole. High Poisson's ratios (0.477 to 0.494) and S-wave attenuation within the LVZ suggest that the LVZ may be composed of highly saturated shales of the Modelo Formation. Because the lateral dimensions of the LVZ approximately correspond to the areas of strongest shaking, we suggest that the highly saturated zone may have contributed to localized strong shaking. Rock sites are generally considered to be ideal locations for site response in urban areas; however, localized, highly saturated rock sites may be a hazard in urban areas that requires further investigation.

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