Shear Wave Velocity Analysis of 2-D Multichannel Analysis of Surface Wave (MASW) to investigate subsurface Fault of Alternative Bridge Construction in Kelok Sago Jambi

2020 ◽  
Vol 25 (1) ◽  
pp. 18-20
Author(s):  
Muhammad Farhan ◽  
◽  
Gunawan Handayani ◽  
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Wave Velocity ◽  
Urban Areas ◽  
Signal To Noise Ratio ◽  
Body Wave ◽  
Geophysical Methods ◽  
P Wave ◽  
S Wave ◽  
Multichannel Analysis

Every geotechnical measurement requires geophysical methods to classify soil types under the ground. S-wave velocity (Vs), P-wave velocity (Vp), and density (ρ), are the most important parameters in the classification of soils. There are various methods to determine Vs, one of them is P-S logging method. However, this method is less suitable to be applied in urban areas due to the difficulties of data acquisition and high expense in operational costs. In 1999, a seismic method uses surface waves to de-termine Vs profile with a higher signal to noise ratio which was known by the name of Multichannel Analysis of Surface Waves (MASW). A surface wave, especially Rayleigh wave, creeps slowly on the surface with a larger amplitude than a body wave. The wavelengths of the surface wave will disperse in the layers system i.e. the phase velocity of the surface waves is now func-tion of frequency. MASW 2-D method is used in this paper to determine subsoil properties and to identify the fault under the bridge abutments plan (abutment 1 and abutment 2) in Kelok Sago Jambi.

Crustal structure of the Iceland region from dispersion of surface waves

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

scholarly journals 3D wave-equation dispersion inversion of surface waves recorded on irregular topography

Geophysics ◽  
2020 ◽  
Vol 85 (3) ◽  
pp. R147-R161 ◽  
Author(s):  
Zhaolun Liu ◽  
Jing Li ◽  
Sherif M. Hanafy ◽  
Kai Lu ◽  
Gerard Schuster
Keyword(s):  
Wave Equation ◽  
Surface Wave ◽  
Surface Waves ◽  
Wave Velocity ◽  
Field Data ◽  
P Wave ◽  
Topographic Effects ◽  
S Wave ◽  
Surface Wave Dispersion ◽  
Irregular Topography

Irregular topography can cause strong scattering and defocusing of propagating surface waves, so it is important to account for such effects when inverting surface waves for shallow S-wave velocity structures. We have developed a 3D surface-wave dispersion inversion method that takes into account the topographic effects modeled by a 3D spectral element solver. The objective function is the frequency summation of the squared wavenumber differences [Formula: see text] along each azimuthal angle of the fundamental mode or higher-order modes of Rayleigh waves in each shot gather. The wavenumbers [Formula: see text] associated with the dispersion curves are calculated using the data recorded along the irregular free surface. Numerical tests on synthetic and field data demonstrate that 3D topographic wave equation dispersion inversion (TWD) can accurately invert for the S-wave velocity model from surface-wave data recorded on irregular topography. Field data tests for data recorded across an Arizona fault demonstrate that, for this example, the 2D TWD model can be as accurate as the 3D tomographic model. This suggests that in some cases, the 2D TWD inversion is preferred over 3D TWD because of its significant reduction in computational costs. Compared to the 3D P-wave velocity tomogram, the 3D S-wave tomogram agrees much more closely with the geologic model taken from the trench log. The agreement with the trench log is even better when the [Formula: see text] tomogram is computed, which reveals a sharp change in velocity across the fault. The localized velocity anomaly in the [Formula: see text] tomogram is in very good agreement with the well log. Our results suggest that integrating the [Formula: see text] and [Formula: see text] tomograms can sometimes give the most accurate estimates of the subsurface geology across normal faults.

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.

Physical Properties and Structure of the Near Subsurface in the Săcel Area, Romania, from Shallow Seismic Measurements

2019 ◽  
Vol 24 (1) ◽  
pp. 151-158
Author(s):  
Ionelia Panea
Keyword(s):  
Wave Velocity ◽  
Signal To Noise Ratio ◽  
Soil Surface ◽  
Geological Structure ◽  
P Wave ◽  
S Wave ◽  
Sedimentary Deposits ◽  
Shallow Seismic ◽  
P Wave Velocity ◽  
Good Signal

Results are presented for shallow seismic reflection measurements performed southwest of Săcel village in Romania for the purpose of obtaining information about the geological structure in the near subsurface. The P-wave and S-wave velocity distributions were also obtained below the soil surface. The measurements were performed along a nearly linear profile on the top of an elongated hill. Most of the shot gathers were characterized by a good signal-to-noise ratio. A depth-converted migrated section was obtained after the processing of shot gathers, on which an image of sedimentary deposits with various thicknesses, separated by shallow faults until a depth of about 80 m, were observed. The P-wave and S-wave velocity-depth models for two segments were of considerable interest for a geotechnical study proposed for the construction of a windmill park. The two- and three-layered P-wave velocity-depth models were comparable until depths of about 10 m after first-arrival traveltime inversions. The lateral variations in the subsurface geological structure and lithology reflected the variations in the P-wave velocity values from both models. The S-wave velocity-depth models for comparable depth intervals were similar to those from the P-wave velocity-depth models. Reliable S-wave velocity distributions were obtained after inversion of fundamental-mode and higher-mode surface waves.

Resolving phase wrapping by using sliding transform for generation of dispersion curves

Geophysics ◽  
2017 ◽  
Vol 82 (3) ◽  
pp. V127-V136 ◽  
Author(s):  
Jyant Kumar ◽  
Tarun Naskar
Keyword(s):  
Spectral Analysis ◽  
Surface Wave ◽  
Surface Waves ◽  
Test Data ◽  
Signal To Noise Ratio ◽  
Phase Unwrapping ◽  
Signal To Noise ◽  
Manual Intervention ◽  
Multichannel Analysis ◽  
Synthetic Test

The complexity involved with the phase unwrapping procedure, while performing the existing spectral analysis of surface waves (SASW) on the basis of two sensors, makes it difficult to automate and requires frequent manual judgment. As a result, this approach generally becomes tedious and may yield erroneous results. The multichannel analysis of surface waves (MASW) technique can resolve the problem of phase wrapping. However, the MASW technique normally requires a large number of closely spaced sensors, typically 24–48 or even more. We have developed a new method that is fast, accurate, and generally resolves the unwrapping of phase with the use of just two sensors, provided the signal-to-noise ratio remains high. In this approach, the unwrapping of the phase can be performed without any manual intervention and an automation of the process becomes feasible. A few examples, involving synthetic test data and surface-wave tests, have been tested to determine the efficacy of our approach. Comparisons of the results have been made with the corresponding solutions using existing SASW and MASW techniques.

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

2019 ◽  
Vol 218 (3) ◽  
pp. 1873-1891 ◽  
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.

Advances in surface-wave tomography for near-surface applications

2021 ◽  
Vol 40 (8) ◽  
pp. 567-575
Author(s):  
Myrto Papadopoulou ◽  
Farbod Khosro Anjom ◽  
Mohammad Karim Karimpour ◽  
Valentina Laura Socco
Keyword(s):  
Surface Wave ◽  
Wave Velocity ◽  
P Wave ◽  
Seismic Exploration ◽  
S Wave ◽  
Data Set ◽  
Near Surface ◽  
Processing Times ◽  
Spatial Coverage ◽  
Wave Tomography

Surface-wave (SW) tomography is a technique that has been widely used in the field of seismology. It can provide higher resolution relative to the classical multichannel SW processing and inversion schemes that are usually adopted for near-surface applications. Nevertheless, the method is rarely used in this context, mainly due to the long processing times needed to pick the dispersion curves as well as the inability of the two-station processing to discriminate between higher SW modes. To make it efficient and to retrieve pseudo-2D/3D S-wave velocity (VS) and P-wave velocity (VP) models in a fast and convenient way, we develop a fully data-driven two-station dispersion curve estimation, which achieves dense spatial coverage without the involvement of an operator. To handle higher SW modes, we apply a dedicated time-windowing algorithm to isolate and pick the different modes. A multimodal tomographic inversion is applied to estimate a VS model. The VS model is then converted to a VP model with the Poisson's ratio estimated through the wavelength-depth method. We apply the method to a 2D seismic exploration data set acquired at a mining site, where strong lateral heterogeneity is expected, and to a 3D pilot data set, recorded with state-of-the-art acquisition technology. We compare the results with the ones retrieved from classical multichannel analysis.

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

Geophysics ◽  
2017 ◽  
Vol 82 (6) ◽  
pp. EN99-EN108 ◽  
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.

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

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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