scholarly journals Characteristics of the horizontal component of Rayleigh waves in multimode analysis of surface waves

Geophysics ◽  
2015 ◽  
Vol 80 (1) ◽  
pp. EN1-EN11 ◽  
Author(s):  
Tatsunori Ikeda ◽  
Toshifumi Matsuoka ◽  
Takeshi Tsuji ◽  
Toru Nakayama
Keyword(s):  
Surface Waves ◽  
Wave Velocity ◽  
Rayleigh Waves ◽  
Field Data ◽  
Vertical Component ◽  
Dispersion Curves ◽  
Horizontal Component ◽  
S Wave ◽  
Higher Modes ◽  
Explosive Source

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.

Wave-equation dispersion inversion of Love waves

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. R693-R705 ◽  
Author(s):  
Jing Li ◽  
Sherif Hanafy ◽  
Zhaolun Liu ◽  
Gerard T. Schuster
Keyword(s):  
Wave Equation ◽  
Wave Velocity ◽  
Rayleigh Waves ◽  
Love Wave ◽  
Field Data ◽  
Wave Dispersion ◽  
Dispersion Curves ◽  
Love Waves ◽  
S Wave ◽  
Love Wave Dispersion

We present a theory for wave-equation inversion of Love-wave dispersion curves, in which the misfit function is the sum of the squared differences between the wavenumbers along the predicted and observed dispersion curves. Similar to inversion of Rayleigh-wave dispersion curves, the complicated Love-wave arrivals in traces are skeletonized as simpler data, namely, the picked dispersion curves in the [Formula: see text] domain. Numerical solutions to the SH-wave equation and an iterative optimization method are then used to invert these dispersion curves for the S-wave velocity model. This procedure, denoted as wave-equation dispersion inversion of Love waves (LWD), does not require the assumption of a layered model or smooth velocity variations, and it is less prone to the cycle-skipping problems of full-waveform inversion. We demonstrate with synthetic and field data examples that LWD can accurately reconstruct the S-wave velocity distribution in a laterally heterogeneous medium. Compared with Rayleigh waves, inversion of the Love-wave dispersion curves empirically exhibits better convergence properties because they are completely insensitive to the P-velocity variations. In addition, Love-wave dispersion curves for our examples are simpler than those for Rayleigh waves, and they are easier to pick in our field data with a low signal-to-noise ratio.

Retrieval of shallow S-wave profiles from seismic reflection surveying and traffic-induced noise

Geophysics ◽  
2020 ◽  
Vol 85 (6) ◽  
pp. EN105-EN117
Author(s):  
Kai Zhang ◽  
Hongyi Li ◽  
Xiaojiang Wang ◽  
Kai Wang
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Wave Velocity ◽  
Rayleigh Waves ◽  
Seismic Reflection ◽  
Seismic Energy ◽  
Dispersion Curves ◽  
S Wave ◽  
Near Surface ◽  
Wave Velocities

In urban subsurface exploration, seismic surveys are mostly conducted along roads where seismic vibrators can be extensively used to generate strong seismic energy due to economic and environmental constraints. Generally, Rayleigh waves also are excited by the compressional wave profiling process. Shear-wave (S-wave) velocities can be inferred using Rayleigh waves to complement near-surface characterization. Most vibrators cannot excite seismic energy at lower frequencies (<5 Hz) to map greater depths during surface-wave analysis in areas with low S-wave velocities, but low-frequency surface waves ([Formula: see text]) can be extracted from traffic-induced noise, which can be easily obtained at marginal additional cost. We have implemented synthetic tests to evaluate the velocity deviation caused by offline sources, finding a reasonably small relative bias of surface-wave dispersion curves due to vehicle sources on roads. Using a 2D reflection survey and traffic-induced noise from the central North China Plain, we apply seismic interferometry to a series of 10.0 s segments of passive data. Then, each segment is selectively stacked on the acausal-to-causal ratio of the mean signal-to-noise ratio to generate virtual shot gathers with better dispersion energy images. We next use the dispersion curves derived by combining controlled source surveying with vehicle noise to retrieve the shallow S-wave velocity structure. A maximum exploration depth of 90 m is achieved, and the inverted S-wave profile and interval S-wave velocity model obtained from reflection processing appear consistent. The data set demonstrates that using surface waves derived from seismic reflection surveying and traffic-induced noise provides an efficient supplementary technique for delineating shallow structures in areas featuring thick Quaternary overburden. Additionally, the field test indicates that traffic noise can be created using vehicles or vibrators to capture surface waves within a reliable frequency band of 2–25 Hz if no vehicles are moving along the survey line.

Window-controlled CMP crosscorrelation analysis for surface waves in laterally heterogeneous media

Geophysics ◽  
2013 ◽  
Vol 78 (6) ◽  
pp. EN95-EN105 ◽  
Author(s):  
Tatsunori Ikeda ◽  
Takeshi Tsuji ◽  
Toshifumi Matsuoka
Keyword(s):  
Surface Waves ◽  
Wave Velocity ◽  
Heterogeneous Media ◽  
Velocity Structure ◽  
Weighting Function ◽  
Dispersion Curves ◽  
Lateral Resolution ◽  
Heterogeneous Structure ◽  
S Wave ◽  
Data Set

CMP crosscorrelation (CMPCC) analysis of surface waves enhances lateral resolution of surface wave analyses. We found the technique of window-controlled CMPCC analysis, which applies two kinds of spatial windows to further improve the lateral resolution of CMPCC analysis. First, a spatial weighting function given by the number of crosscorrelation pairs is applied to CMPCC gathers. Because the number of crosscorrelation pairs is concentrated near the CMP, the lateral resolution in extracting dispersion curves on CMPs can be improved. Second, crosscorrelation pairs with longer receiver spacing are excluded to further improve lateral resolution. Although removing crosscorrelation pairs generally decreases the accuracy of phase velocity estimations, the required accuracy to estimate phase velocities is maintained by considering the wavenumber resolution defined for given receiver configurations. When applied to a synthetic data set simulating a laterally heterogeneous structure, window-controlled CMPCC analysis improved the retrieval of the lateral variation in local dispersion curves beneath each CMP. We also applied the method to field seismic data across a major fault. The window-controlled CMPCC analysis improved lateral variations of the inverted S-wave velocity structure without degrading the accuracy of S-wave velocity estimations. We discovered that window-controlled CMPCC analysis is effective in improving lateral resolution of dispersion curve estimations with respect to the original CMPCC analysis.

scholarly journals Seismic Ambient Noise Imaging of a Quasi-Amagmatic Ultra-Slow Spreading Ridge

2021 ◽  
Vol 13 (14) ◽  
pp. 2811
Author(s):  
Mohamadhasan Mohamadian Sarvandani ◽  
Emanuel Kästle ◽  
Lapo Boschi ◽  
Sylvie Leroy ◽  
Mathilde Cannat
Keyword(s):  
Wave Velocity ◽  
Vertical Component ◽  
Velocity Model ◽  
Dispersion Curves ◽  
Southwest Indian Ridge ◽  
Spreading Ridge ◽  
Ocean Bottom ◽  
S Wave ◽  
Crust And Upper Mantle ◽  
Phase Velocity Dispersion

Passive seismic interferometry has become very popular in recent years in exploration geophysics. However, it has not been widely applied in marine exploration. The purpose of this study is to investigate the internal structure of a quasi-amagmatic portion of the Southwest Indian Ridge by interferometry and to examine the performance and reliability of interferometry in marine explorations. To reach this goal, continuous vertical component recordings from 43 ocean bottom seismometers were analyzed. The recorded signals from 200 station pairs were cross-correlated in the frequency domain. The Bessel function method was applied to extract phase–velocity dispersion curves from the zero crossings of the cross-correlations. An average of all the dispersion curves was estimated in a period band 1–10 s and inverted through a conditional neighborhood algorithm which led to the final 1D S-wave velocity model of the crust and upper mantle. The obtained S-wave velocity model is in good agreement with previous geological and geophysical studies in the region and also in similar areas. We find an average crustal thickness of 7 km with a shallow layer of low shear velocities and high Vp/Vs ratio. We infer that the uppermost 2 km are highly porous and may be strongly serpentinized.

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.

Near-surface velocity structure study using surface waves and first breaks in the middle segment of the Bangong-Nujiang suture zone, Tibetan Plateau

2020 ◽  
Author(s):  
Hui Zhang ◽  
Rizheng He ◽  
Zhiwei Liu
Keyword(s):  
Surface Waves ◽  
Wave Velocity ◽  
Velocity Structure ◽  
Dispersion Curves ◽  
Suture Zone ◽  
Surface Velocity ◽  
S Wave ◽  
Middle Segment ◽  
Near Surface ◽  
Order Dispersion

&lt;p&gt;The Bangong-Nujiang suture zone, located in the central Tibet, is one of several important geological boundaries in Qinghai-Tibet plateau. Abundant researches have been performed and most of them focused on deep tectonic structure and its dynamic mechanism through recent geophysical projects such as INDEPTH-III, Hi-CLIMB, ANTILOPE, SinoProbe, etc. (Zhao Wenjin et al., 2008; N&amp;#180;abelek et al. 2009; Gao Rui, et al., 2013;Zhao Junmeng et al. 2014; He Rizheng et al., 2014; Xu Qiang et al., 2017; Shang Xuefeng et al., 2017; Davlatkhudzha et al.,2018). Near-surface velocity study can not only obtain the physical parameters such as Vp and Vs in the area, but also improve seismic image quality of deep structure (Zhao Lingzhi et al., 2018). However, the velocity information obtained from passive seismic stations using either receiver function or ambient noise tomography is not enough to elaborate the near surface velocity structure of the Bangong-Nujiang suture zone. Besides, the active-source seismic reflection data usually doesn&amp;#8217;t have sufficient offset density at near surface which poses a challenge to conventional near-surface velocity analysis methods.&lt;/p&gt;&lt;p&gt;This study makes full use of surface waves and first breaks to obtain near-surface P- and S-wave velocities based on a 2D deep seismic reflection survey data which was acquired by SinoProbe project in 2009 . We adopt the method of superposition of surface waves in common receiver domain to generate high quality F-K spectrum which enables us to obtain fundamental-order and high-order dispersion curves. First, a 2D layered model with an irregular topography was built and the 2D elastic finite difference modeling was executed to generate 161 synthetic seismic shot gathers which mimicking the actual acquisition geometry. These gathers contain surface waves, refractions, reflections and multiples energy, and the maximum offset is about 18 km. It is shown that the F-K spectrum quality has been improved for each receiver station using superposition of surface waves in the F-K domain by adding more shots. The S-wave velocity inverted from dispersion curves showed good agreement with&amp;#160;the&amp;#160;synthetic model. Second, high quality F-K spectrum generated from the above method enabled us to pick both fundamental and 1&lt;sup&gt;st&lt;/sup&gt; order dispersion curves from the SinoProbe field data. The S-wave velocity was generated using three methods: 1) empirical equations based on dispersion curves; 2) fundamental order dispersion curves inversion; and 3) both fundamental and 1&lt;sup&gt;st &lt;/sup&gt;order dispersion curves inversion. Results show that using higher order dispersion curves can generate a more reliable near-surface model. Third, first breaks were picked up to 18 km offset and diving wave tomography was applied to derive near-surface P-wave velocity from abundant first break information. It is shown that there is an excellent correlation between P- and S-wave velocities, the bottom of basin is clearly revealed, and over-thrusts are identified accordingly which is consistent with field geological survey in the middle segment of Bangong-Nujiang suture zone.&lt;/p&gt;&lt;p&gt;This study was financially supported by the CAGS Research Fund (grant YWF201907), and the National Natural Science Foundation of China (grant 41761134094). Data sources: SinoProbe-02 Project.&lt;/p&gt;

scholarly journals Metode Seismik dalam Pemodelan Fisis Letusan Gunung Lumpur Bledug Kuwu

2019 ◽  
Vol 2 (2) ◽  
pp. 61-66
Author(s):  
Ahmad Fauzi Pohan ◽  
Rusnoviandi Rusnoviandi
Keyword(s):  
Wave Velocity ◽  
Physical Modeling ◽  
Vertical Component ◽  
Dominant Frequency ◽  
P Wave ◽  
Physical Parameters ◽  
S Wave ◽  
Interesting Phenomenon ◽  
Central Java ◽  
P Wave Velocity

Aktivitas gunung lumpur Bledug Kuwu di Jawa  Tengah merupakan fenomena yang menarik dikaji menggunakan pemodelan fisis. Tujuan penelitian ini adalah mengetahui parameter dari medium gunung lumpur Bledug Kuwu. Adapun pemodelan fisis yang dilakukan dengan menggunakan media fisis akuarium berukuran 59 × 59 × 37,3 cm yang diisi material dari lumpur Bledug Kuwu. Sumber letusan dihasilkan dari tekanan kompresor yang dapat diatur kedalaman (10.5, 13, dan 15.5 cm) dan sudut (30o, 45o dan 60o) sumbernya. Sensor yang digunakan geophone komponen vertikal sebanyak 3 buah dengan durasi perekaman selama 5 dan 2,5 detik. Data diambil dengan frekuensi sampel 2 dan 4 kHz untuk masing-masing durasi perekaman. Konfigurasi sumber dan geophone dibuat sesuai dengan pemodelan fisisnya. Pengukuran desnsitas lumpur menunjukkan angka sebesar 1200 kg/m3. Berdasarkan hasil analisis seismogram model fisis diperoleh kecepatan perambatan gelombang-P pada medium lumpur Bledug Kuwu adalah sebesar 48,74 m/s,dan gelombang-S sebesar 28,14 m/s dengan frekuensi dominan antara 20 sampai 25 Hz.   Bledug Kuwu mud volcano activity in Central Java is an interesting phenomenon to be studied using both physical  modeling. The objective of this study was to determine the physical parameters of the medium of Bledug Kuwu. The Physical model was an aquarium with a dimension of 59 × 59 × 37.3 cm filled with Bledug Kuwu’s mud. The eruption source is generated by a compressor pressure that can be controled both the depth(10.5, 13, and 15.5 cm) and the angel of the source (30o, 45o and 60o). The resulting seismic signals were recorded by using 3 vertical component geophones for 10 and 5 seconds durations at a frequency of 2 and 4 kHz respectivel, mud density 1200 kg/m3 . The physical modeling shows that the P-wave velocity of the Bledug Kuwu’s medium is 48.7 m/s, S-wave velocity of Bledug Kuwu’s is 28,14 m/s  with a dominant frequency of 20 to 25 Hz.

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
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