3D S-wave velocity modelling with surface waves in oil seismic prospecting

In surface-wave analysis, S-wave velocity estimations can be improved by the use of higher modes of the surface waves. The vertical component of P-SV waves is commonly used to estimate multimode Rayleigh waves, although Rayleigh waves are also included in horizontal components of P-SV waves. To demonstrate the advantages of using the horizontal components of multimode Rayleigh waves, we investigated the characteristics of the horizontal and vertical components of Rayleigh waves. We conducted numerical modeling and field data analyses rather than a theoretical study for both components of Rayleigh waves. As a result of a simulation study, we found that the estimated higher modes have larger relative amplitudes in the vertical and horizontal components as the source depth increases. In particular, higher-order modes were observed in the horizontal component data for an explosive source located at a greater depth. Similar phenomena were observed in the field data acquired by using a dynamite source at 15-m depth. Sensitivity analyses of dispersion curves to S-wave velocity changes revealed that dispersion curves additionally estimated from the horizontal components can potentially improve S-wave velocity estimations. These results revealed that when the explosive source was buried at a greater depth, the horizontal components can complement Rayleigh waves estimated from the vertical components. Therefore, the combined use of the horizontal component data with the vertical component data would contribute to improving S-wave velocity estimations, especially in the case of buried explosive source signal.

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Full-waveform matching of VP and VS models from surface waves

Geophysical Journal International ◽

10.1093/gji/ggz279 ◽

2019 ◽

Vol 218 (3) ◽

pp. 1873-1891 ◽

Cited By ~ 2

Author(s):

Farbod Khosro Anjom ◽

Daniela Teodor ◽

Cesare Comina ◽

Romain Brossier ◽

Jean Virieux ◽

...

Keyword(s):

Surface Waves ◽

Wave Velocity ◽

Real Data ◽

Test Site ◽

P Wave ◽

S Wave ◽

Surface Wave Dispersion ◽

Data Set ◽

Near Surface ◽

Velocity Models

SUMMARY The analysis of surface wave dispersion curves (DCs) is widely used for near-surface S-wave velocity (VS) reconstruction. However, a comprehensive characterization of the near-surface requires also the estimation of P-wave velocity (VP). We focus on the estimation of both VS and VP models from surface waves using a direct data transform approach. We estimate a relationship between the wavelength of the fundamental mode of surface waves and the investigation depth and we use it to directly transform the DCs into VS and VP models in laterally varying sites. We apply the workflow to a real data set acquired on a known test site. The accuracy of such reconstruction is validated by a waveform comparison between field data and synthetic data obtained by performing elastic numerical simulations on the estimated VP and VS models. The uncertainties on the estimated velocity models are also computed.

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

Bulletin of the Seismological Society of America ◽

10.1785/0120200272 ◽

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.

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Crustal structure of the Iceland region from dispersion of surface waves

Bulletin of the Seismological Society of America ◽

10.1785/bssa0520020359 ◽

1962 ◽

Vol 52 (2) ◽

pp. 359-388

Author(s):

Eysteinn Tryggvason

Keyword(s):

Surface Layer ◽

Surface Wave ◽

Surface Waves ◽

Wave Velocity ◽

Crustal Structure ◽

Wave Dispersion ◽

P Wave ◽

S Wave ◽

Surface Wave Dispersion ◽

Mid Atlantic Ridge

ABSTRACT A number of Icelandic records of earthquakes originating in the Mid-Atlantic Seismic Belt between 52° and 70° N. lat. have been investigated. The surface waves on these records are chiefly in the period interval 3–10 sec, and are first mode Love-waves and Rayleigh-waves. The surface wave dispersion can be explained by a three-layered crustal structure as follows. A surface layer of S-wave velocity about 2.7 km/sec covering the whole region studied, a second layer of S-wave velocity about 3.6 km/sec covering Iceland and extending several hundred kilometers off the coasts and a third layer of S-wave velocity about 4.3 km/sec and P-wave velocity about 7.4 km/sec underlying the whole region. The thickness of the surface layer appears to be about 4 km on the Mid-Atlantic Ridge south of Iceland and in western Iceland, 3 km in central Iceland and 7 km northwest of Iceland. The second layer is apparently of similar thickness than the surface layer, while the third layer is thick; and the surface wave dispersion does not indicate any layer of higher wave velocity. This 7.4-layer is supposed to belong to the mantle, although its wave velocity is significantly lower than usually found in the upper mantle

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Wave-equation Rayleigh-wave dispersion inversion using fundamental and higher modes

Geophysics ◽

10.1190/geo2018-0506.1 ◽

2019 ◽

Vol 84 (4) ◽

pp. EN57-EN65 ◽

Cited By ~ 7

Author(s):

Zhen-Dong Zhang ◽

Tariq Alkhalifah

Keyword(s):

Wave Equation ◽

Rayleigh Wave ◽

Surface Waves ◽

Wave Velocity ◽

Minimum Problem ◽

Velocity Spectrum ◽

Local Similarity ◽

Inversion Algorithm ◽

S Wave ◽

Near Surface

Recorded surface waves often provide reasonable estimates of the S-wave velocity in the near surface. However, existing algorithms are mainly based on the 1D layered-model assumption and require picking the dispersion curves either automatically or manually. We have developed a wave-equation-based inversion algorithm that inverts for S-wave velocities using fundamental and higher mode Rayleigh waves without picking an explicit dispersion curve. Our method aims to maximize the similarity of the phase velocity spectrum ([Formula: see text]) of the observed and predicted surface waves with all Rayleigh-wave modes (if they exist) included in the inversion. The [Formula: see text] spectrum is calculated using the linear Radon transform applied to a local similarity-based objective function; thus, we do not need to pick velocities in spectrum plots. As a result, the best match between the predicted and observed [Formula: see text] spectrum provides the optimal estimation of the S-wave velocity. We derive S-wave velocity updates using the adjoint-state method and solve the optimization problem using a limited-memory Broyden-Fletcher-Goldfarb-Shanno algorithm. Our method excels in cases in which the S-wave velocity has vertical reversals and lateral variations because we used all-modes dispersion, and it can suppress the local minimum problem often associated with full-waveform inversion applications. Synthetic and field examples are used to verify the effectiveness of our method.

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A comprehensive comparison between the refraction microtremor and seismic interferometry methods for phase-velocity estimation

Geophysics ◽

10.1190/geo2016-0654.1 ◽

2017 ◽

Vol 82 (6) ◽

pp. EN99-EN108 ◽

Cited By ~ 7

Author(s):

Zongbo Xu ◽

T. Dylan Mikesell ◽

Jianghai Xia ◽

Feng Cheng

Keyword(s):

Surface Wave ◽

Surface Waves ◽

Wave Velocity ◽

Velocity Estimation ◽

Seismic Interferometry ◽

S Wave ◽

Noise Sources ◽

Surface Wave Dispersion ◽

Near Surface ◽

Refraction Microtremor

Passive-source seismic-noise-based surface-wave methods are now routinely used to investigate the near-surface geology in urban environments. These methods estimate the S-wave velocity of the near surface, and two methods that use linear recording arrays are seismic interferometry (SI) and refraction microtremor (ReMi). These two methods process noise data differently and thus can yield different estimates of the surface-wave dispersion, the data used to estimate the S-wave velocity. We have systematically compared these two methods using synthetic data with different noise source distributions. We arrange sensors in a linear survey grid, which is conveniently used in urban investigations (e.g., along roads). We find that both methods fail to correctly determine the low-frequency dispersion characteristics when outline noise sources become stronger than inline noise sources. We also identify an artifact in the ReMi method and theoretically explain the origin of this artifact. We determine that SI combined with array-based analysis of surface waves is the more accurate method to estimate surface-wave phase velocities because SI separates surface waves propagating in different directions. Finally, we find a solution to eliminate the ReMi artifact that involves the combination of SI and the [Formula: see text]-[Formula: see text] transform, the array processing method that underlies the ReMi method.

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Two-Dimensional Full-Waveform Joint Inversion of Surface Waves Using Phases and Z/H Ratios

Applied Sciences ◽

10.3390/app11156712 ◽

2021 ◽

Vol 11 (15) ◽

pp. 6712

Author(s):

Chao Zhang ◽

Ting Lei ◽

Yi Wang

Keyword(s):

Surface Wave ◽

Surface Waves ◽

Wave Velocity ◽

Joint Inversion ◽

Waveform Inversion ◽

Small Scale ◽

Imaging Method ◽

S Wave ◽

Surface Wave Dispersion ◽

Full Waveform

Surface-wave dispersion and the Z/H ratio are important parameters used to resolve the Earth’s structure, especially for S-wave velocity. Several previous studies have explored using joint inversion of these two datasets. However, all of these studies used a 1-D depth-sensitivity kernel, which lacks precision when the structure is laterally heterogeneous. Adjoint tomography (i.e., full-waveform inversion) is a state-of-the-art imaging method with a high resolution. It can obtain better-resolved lithospheric structures beyond the resolving ability of traditional ray-based travel-time tomography. In this study, we present a systematic investigation of the 2D sensitivities of the surface wave phase and Z/H ratio using the adjoint-state method. The forward-modeling experiments indicated that the 2D phase and Z/H ratio had different sensitivities to the S-wave velocity. Thus, a full-waveform joint-inversion scheme of surface waves with phases and a Z/H ratio was proposed to take advantage of their complementary sensitivities to the Earth’s structure. Both applications to synthetic data sets in large- and small-scale inversions demonstrated the advantage of the joint inversion over the individual inversions, allowing for the creation of a more unified S-wave velocity model. The proposed joint-inversion scheme offers a computationally efficient and inexpensive alternative to imaging fine-scale shallow structures beneath a 2D seismic array.

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