Improving surface‐wave group velocity measurements by energy reassignment

Geophysics ◽  
2003 ◽  
Vol 68 (2) ◽  
pp. 677-684 ◽  
Author(s):  
Helle A. Pedersen ◽  
Jérôme I. Mars ◽  
Pierre‐Olivier Amblard
Keyword(s):  
Surface Waves ◽  
Dispersion Curve ◽  
Group Velocity ◽  
Shear Wave ◽  
Group Velocity Dispersion ◽  
Seismic Survey ◽  
Earth Model ◽  
Velocity Measurements ◽  
Time Frequency ◽  
Shallow Seismic

Surface waves are increasingly used for shallow seismic surveys—in particular, in acoustic logging, environmental, and engineering applications. These waves are dispersive, and their dispersion curves are used to obtain shear velocity profiles with depth. The main obstacle to their more widespread use is the complexity of the associated data processing and interpretation of the results. Our objective is to show that energy reassignment in the time–frequency domain helps improve the precision of group velocity measurements of surface waves. To show this, full‐waveform seismograms with added white noise for a shallow flat‐layered earth model are analyzed by classic and reassigned multiple filter analysis (MFA). Classic MFA gives the expected smeared image of the group velocity dispersion curve, while the reassigned curve gives a very well‐constrained, narrow dispersion curve. Systematic errors from spectral fall‐off are largely corrected by the reassignment procedure. The subsequent inversion of the dispersion curve to obtain the shear‐wave velocity with depth is carried out through a procedure combining linearized inversion with a nonlinear Monte Carlo inversion. The diminished uncertainty obtained after reassignment introduces significantly better constraints on the earth model than by inverting the output of classic MFA. The reassignment is finally carried out on data from a shallow seismic survey in northern Belgium, with the aim of determining the shear‐wave velocities for seismic risk assessment. The reassignment is very stable in this case as well. The use of reassignment can make dispersion measurements highly automated, thereby facilitating the use of surface waves for shallow surveys.

Noncontact Evaluation of Defects in Thin Plate With Multimodes Lamb’s Waves and Wavelet Transform

2002 ◽  
Author(s):  
Morimasa Murase ◽  
Koichiro Kawashima
Keyword(s):  
Group Velocity ◽  
Thin Plate ◽  
Wavelet Transformation ◽  
Velocity Dispersion ◽  
Lamb Waves ◽  
Group Velocity Dispersion ◽  
Dispersion Curves ◽  
Contact Method ◽  
Intact Specimen ◽  
Time Frequency

Multimode’s Lamb waves in aluminum plates with various defects were excited by a Q-switched Nd:YAG laser. The Lamb waves past through the defects were received a laser interferometer. The received signals of the Lamb waves are processed by the wavelet transformation. The wavelet transformation is generally shown on the time-frequency domain. By dividing a propagation distance by the time, the group velocities are identified. In this way, group velocity dispersion maps of multimode’s Lamb waves are constructed with the received temporal signals. By changing the shape of the mother wavelet, Gabor function, we can identify the dispersion curves of the higher mode Lamb waves. The group velocity dispersion maps of a intact specimen agree well on theoretical dispersion curves of S0, A0, S1, A1, S2, A2, and A3 modes. The difference between the dispersion maps of the intact specimen and that with defects clearly visualizes the existence of defects. This non-contact method is effective for inspecting various defects in thin plate structures.

Extracting Long-Period Surface Waves and Free Oscillations Using Ambient Noise Recorded by Global Distributed Superconducting Gravimeters

2020 ◽  
Vol 91 (4) ◽  
pp. 2234-2246
Author(s):  
Hang Li ◽  
Jianqiao Xu ◽  
Xiaodong Chen ◽  
Heping Sun ◽  
Miaomiao Zhang ◽  
...  
Keyword(s):  
Surface Waves ◽  
Group Velocity ◽  
Ambient Noise ◽  
Velocity Dispersion ◽  
Group Velocity Dispersion ◽  
Dispersion Curves ◽  
Free Oscillations ◽  
Long Period ◽  
Superconducting Gravimeters ◽  
Noise Data

Abstract Inversion of internal structure of the Earth using surface waves and free oscillations is a hot topic in seismological research nowadays. With the ambient noise data on seismically quiet days sourced from the gravity tidal observations of seven global distributed superconducting gravimeters (SGs) and the seismic observations for validation from three collocated STS-1 seismometers, long-period surface waves and background free oscillations are successfully extracted by the phase autocorrelation (PAC) method, respectively. Group-velocity dispersion curves at the frequency band of 2–7.5 mHz are extracted and compared with the theoretical values calculated with the preliminary reference Earth model. The comparison shows that the best observed values differ about ±2% from the corresponding theoretical results, and the extracted group velocities of the best SG are consistent with the result of the collocated STS-1 seismometer. The results indicate that reliable group-velocity dispersion curves can be measured with the ambient noise data from SGs. Furthermore, the fundamental frequency spherical free oscillations of 2–7 mHz are also clearly extracted using the same ambient noise data. The results in this study show that the SG, besides the seismometer, is proved to be another kind of instrument that can be used to observe long-period surface waves and free oscillations on seismically quiet days with a high degree of precision using the PAC method. It is worth mentioning that the PAC method is first and successfully introduced to analyze SG observations in our study.

Observation of Higher-Mode Surface Waves from an Active Source in the Hutubi Basin, Xinjiang, China

2021 ◽  
Author(s):  
Zhanbo Ji ◽  
Baoshan Wang ◽  
Wei Yang ◽  
Weitao Wang ◽  
Jinbo Su ◽  
...  
Keyword(s):  
Surface Waves ◽  
Wave Velocity ◽  
Seismic Waves ◽  
Velocity Structure ◽  
Group Velocity Dispersion ◽  
S Wave ◽  
Contributing Factors ◽  
Low Velocity ◽  
Time Frequency ◽  
Wave Modes

ABSTRACT Basins with thick sediments can amplify and prolong the incoming seismic waves, which may cause serious damage to surface facilities. The amplification of seismic energy depends on the shear-wave velocity of the uppermost layers, which is generally estimated through surface wave analysis. Surface waves may propagate in different modes, and the mechanism of the mode development is not well understood. Exploiting a recently deployed permanent airgun source in the Hutubi basin, Xinjiang, northwest China, we conducted a field experiment to investigate the development of multimode surface waves. We observed surface waves at the frequency of 0.3–5.0 Hz with apparent group velocities of 200–900  m/s, and identified five modes of surface waves (three Rayleigh-wave modes and two Love-wave modes) through time–frequency and particle-motion analyses. We then measured 125 group velocity dispersion curves of the fundamental- and higher-mode surface waves, and further inverted the 1D S-wave velocity structure of the Hutubi basin. The S-wave velocity increases abruptly from 238  m/s at the surface to 643  m/s at 300 m depth. Synthetic seismograms with the inverted velocity structure capture the main features of the surface waves of the different modes. Synthetic tests suggest that the low velocity, high velocity gradient, and shallow source depth are likely the dominant contributing factors in the development of higher-mode surface waves.

Multichannel analysis of surface waves

Geophysics ◽  
1999 ◽  
Vol 64 (3) ◽  
pp. 800-808 ◽  
Author(s):  
Choon B. Park ◽  
Richard D. Miller ◽  
Jianghai Xia
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Dispersion Curve ◽  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Frequency Component ◽  
Multichannel Recording ◽  
Phase Velocities ◽  
Ground Roll

The frequency‐dependent properties of Rayleigh‐type surface waves can be utilized for imaging and characterizing the shallow subsurface. Most surface‐wave analysis relies on the accurate calculation of phase velocities for the horizontally traveling fundamental‐mode Rayleigh wave acquired by stepping out a pair of receivers at intervals based on calculated ground roll wavelengths. Interference by coherent source‐generated noise inhibits the reliability of shear‐wave velocities determined through inversion of the whole wave field. Among these nonplanar, nonfundamental‐mode Rayleigh waves (noise) are body waves, scattered and nonsource‐generated surface waves, and higher‐mode surface waves. The degree to which each of these types of noise contaminates the dispersion curve and, ultimately, the inverted shear‐wave velocity profile is dependent on frequency as well as distance from the source. Multichannel recording permits effective identification and isolation of noise according to distinctive trace‐to‐trace coherency in arrival time and amplitude. An added advantage is the speed and redundancy of the measurement process. Decomposition of a multichannel record into a time variable‐frequency format, similar to an uncorrelated Vibroseis record, permits analysis and display of each frequency component in a unique and continuous format. Coherent noise contamination can then be examined and its effects appraised in both frequency and offset space. Separation of frequency components permits real‐time maximization of the S/N ratio during acquisition and subsequent processing steps. Linear separation of each ground roll frequency component allows calculation of phase velocities by simply measuring the linear slope of each frequency component. Breaks in coherent surface‐wave arrivals, observable on the decomposed record, can be compensated for during acquisition and processing. Multichannel recording permits single‐measurement surveying of a broad depth range, high levels of redundancy with a single field configuration, and the ability to adjust the offset, effectively reducing random or nonlinear noise introduced during recording. A multichannel shot gather decomposed into a swept‐frequency record allows the fast generation of an accurate dispersion curve. The accuracy of dispersion curves determined using this method is proven through field comparisons of the inverted shear‐wave velocity ([Formula: see text]) profile with a downhole [Formula: see text] profile.

Crustal architecture of Amsterdam-St. Paul Island from an integrated geophysical approach

2021 ◽  
Author(s):  
Pankaj Kumar ◽  
Pratyush Anand ◽  
Dibakar Ghosal ◽  
Pabitra Singha
Keyword(s):  
Magnetic Material ◽  
Rayleigh Wave ◽  
Dispersion Curve ◽  
Group Velocity ◽  
Velocity Dispersion ◽  
Receiver Function ◽  
Group Velocity Dispersion ◽  
Joint Inversion ◽  
Wave Group ◽  
Magnetic Model

<p>The Amsterdam-St. Paul (ASP) island complex is a manifestation of interaction between the South-East Indian Ridge (SEIR) and the ASP mantle plume, which was formed ~10 Ma. Very few geophysical studies have been conducted over the ASP island complex and therefore we have limited information about the island so far. We performed an integrated geophysical approach using gravity, magnetic study along with the joint inversion of Ps receiver function and Rayleigh wave group velocity dispersion curve to determine the crustal architecture and Moho variation in the region. The result of integrated gravity-magnetic modeling revealed that the island complex is associated with three crustal layers beneath the sedimentary strata. Inversion of Rayleigh wave group velocity dispersion curve accounts for vertical shear wave velocity average which supported the layered velocity profile. The results revealed that magnetic material (Mid oceanic ridge basalt/Flood basalt) has carpeted the entire island causing high magnetic anomaly of -1000 to 1500 nT, which is generated by gradual accumulation of a thick pile of magnetic material of normal as well as reverse polarity. The results by integrated Gravity-magnetic model suggest that crust beneath the island is suggested to be highly affected by volcanic activity (Mantle Plume/Ridge) and is underlain by high-density underplated material. The results further suggest that SEIR has less role for the outpoured magmatic activity. Integrated Gravity-magnetic model show that Moho is variable beneath the island complex and lies in the range of ~12-17 km. Further results by joint inversion of Ps receiver function and Rayleigh wave group velocity dispersion curve for the station (AIS : Nouvelle Amsterdam - TAAF, France) suggest Moho depth of ~14 km beneath the Amsterdam island and is well in agreement with the gravity-magnetic studies. The result clearly indicates that ASP island complex is highly affected by the ASP plume activity and was evolved during the ridge-plume interaction.</p>

A method for relocating seismic events using surface waves

1973 ◽  
Vol 63 (4) ◽  
pp. 1305-1313
Author(s):  
S. T. Crough ◽  
R. Van der Voo
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Group Velocity ◽  
Group Velocity Dispersion ◽  
Body Wave ◽  
Test Site ◽  
Seismic Events ◽  
Computer Technique ◽  
Nuclear Explosions ◽  
Reference Event

abstract Seismic events can be relocated relative to a reference event by using the group-velocity dispersion curves of surface waves. Since group velocity is a function of the travel path, surface waves from two events in the same locale should show identical group velocities when viewed at any one seismograph station. A computer technique has been developed for comparing the group-velocity curves of any event with the curves of a reference event and for determining the relocation which causes the curves to best coincide. The method is evaluated by relocating eight intermediate-size nuclear explosions of the Nevada Test Site series. With precise curve fitting, the surface-wave locations are slightly more accurate in southern Nevada than the standard body-wave determinations. The surface-wave origin times are considerably more accurate. In areas of sparse station coverage or of many small earthquakes, the surface-wave method can be expected to improve seismic locations significantly.

scholarly journals An extraction method of dispersion curve from vertical seismic profiling data

2020 ◽  
Author(s):  
Zhi Hu ◽  
Jinghuai Gao ◽  
Yanbin He ◽  
Guowei Zhang
Keyword(s):  
Dispersion Curve ◽  
Group Velocity ◽  
Body Wave ◽  
Seismic Signal ◽  
Time Frequency ◽  
Seismic Profiling ◽  
Vertical Seismic Profiling ◽  
Wave Data ◽  
Vsp Data ◽  
The Relationship

Abstract The dispersion curve describes the relationship between velocities and frequencies. The group velocity is a kind of dispersion, which presents the velocities of the energy with different frequencies. Although many studies have shown methods for estimating group velocity from a surface wave, the estimation of group velocity from body-wave data is still hard. In this paper, we propose a method to calculate the group velocity from vertical seismic profiling (VSP) data that is a kind of body-wave data. The generalised S-transform (GST) is used to map the seismic signal to the time-frequency (TF) domain and then the group delay (GD) can be extracted from the TF domain. The GD shows the travelling time of different frequency components. The group velocity can be calculated by the GD and the distance between receivers. Unfortunately, the GD is hard to measure accurately because of the noise. Inaccurate GD introduces errors in estimating the velocity. To reduce the errors, we make use of the multiple traces and the iterative least-squares fitting to extract the relationship line between GD and depths. The slope of the line is the reciprocal of the group velocity. Two numerical examples prove the effectiveness of the method. We also derive the formula of group velocity in diffusive-viscous media. In the field data example, the dispersion intensity at different depths and the geological layers can be well matched. These examples illustrate the proposed method is an alternative method for dispersion estimation from VSP.

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