Seismic interferometry analysis of short-period microtremor observed with a linear array for estimating two-dimensional shallow S-wave velocity structures -An experiment in a ground of Iwate University-

2019 ◽  
Vol 72 (0) ◽  
pp. 17-24
Author(s):  
Hidekazu Yamamoto ◽  
Kyosuke Sasaki ◽  
Tsuyoshi Saito
Keyword(s):  
Wave Velocity ◽  
Linear Array ◽  
Seismic Interferometry ◽  
Two Dimensional ◽  
S Wave ◽  
Short Period

Application of passive and active seismic methods to subsurface investigation of Just-Tegoborze landslide (Outer Carpathians, Poland)

2020 ◽  
Author(s):  
Paulina Harba ◽  
Krzysztof Krawiec
Keyword(s):  
Wave Velocity ◽  
Seismic Noise ◽  
Slip Surface ◽  
Seismic Refraction ◽  
Seismic Interferometry ◽  
Geological Medium ◽  
S Wave ◽  
Passive Seismic ◽  
Outer Carpathians ◽  
Velocity Changes

<p>The study presents the results of seismic measurements on the Just-Tegoborze landslide located in Outer Carpathians in the southern region of Poland. The aim of the study was to investigate the landslide geological subsurface and define S-wave velocity changes within geological medium using passive seismic interferometry (SI) and active multichannel analysis of surface waves (MASW). Additionally, seismic refraction and numerical slip surface calculations were carried out in order to combine the results.</p><p>Measurements of SI were conducted based on local high-frequency seismic noise generated by heavy vehicles passing state road which intersects Just-Tegoborze landslide. Seismic noise registration was made using three-component broadband seismometers installed along a seismic profile. Measurements were repeated in a few series in different season and hydration conditions.</p><p>Seismic sections show different velocity layers within the landslide medium. Comparing them with geological cross-section of the studied area, we can distinguish the main lithological boundaries. First near-surface seismic layers may correspond to clayey colluvium and clayey-rock colluvium. The deepest seismic layer probably correlates to less weathered flysch bedrock made of shales and sandstones. It can be identified as the main slip surface of the studied landslide.</p><p>S-wave velocities within seismic profiles significantly varies between each measurement series of SI. It can be observed a decrease of S-wave velocity in March and July which is connected to seasonal weather and hydration conditions. Strong increase of hydration during melting snow cover in March and after heavy rainfalls in July resulted in loss of rigidity what presumably led to drop of S-wave velocity. Changes in hydration could also cause the variation of the course of the less weathered flysch bedrock boundary.</p><p>Presented results of passive seismic interferometry measurements show that study of seismic noise can be applicable to subsurface identification of an active landslide. The example of Just-Tegoborze site indicates that based on seismic interferometry it is possible to observe changes in elastic properties of geological medium. It is worth to underline that SI and MASW complement each other in retrieving the information of Rayleigh surface wave. Combining the results with seismic refraction and numerical calculations allows to better image the landslide geological subsurface. Such observations may be helpful in assessing landslide threat.</p>

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.

The CMP Cross-Correlation Method and its Limitation

2013 ◽  
Vol 353-356 ◽  
pp. 2153-2158
Author(s):  
Jian Qi Lu ◽  
Shan You Li ◽  
Wei Li
Keyword(s):  
Velocity Profile ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Cross Correlation ◽  
Earth Model ◽  
Two Dimensional ◽  
Layer Model ◽  
S Wave ◽  
One Dimensional ◽  
Shallow Site

The MASW method is robust in determine shear wave velocity of shallow site because the dispersive properties of Rayleigh wave was dominated by shear wave velocity of subsurface. Using this method, an assumption that the earth model is one dimensional and horizontal layered must be put to simplify the real earth model without considering the lateral variation. However, it is not always the truth. In order to obtain a two dimensional S-wave velocity profile of shallow site, a CMP cross-correlation (CMPCC) method was proposed by Hayashi and Suzuki (2004) to approximate two dimensional S-wave velocity profile with one dimensional inversion procedure. In order to verify its approximate resolution, a horizontal stepped layer model and a dipping layer model were chosen. The synthetic wave fields of the two models were calculated by staggered grid finite difference method. Result shows that this method can only be used to approximate horizontally stepped layer model and cannot be used to approximate dipping layer model.

Statistics on the Performance of Instrument Types and the Significance of HVSR data for Shallow Vs HVSR/DC Joint Inversions - A Result from the Large-N Maupasacq Experiment (Southern France)

2020 ◽  
Author(s):  
Maik Neukirch ◽  
Antonio García-Jerez ◽  
Antonio Villaseñor ◽  
Laurent Stehly ◽  
Pierre Boué ◽  
...  
Keyword(s):  
Wave Velocity ◽  
Large Scale ◽  
Group Velocity Dispersion ◽  
Joint Inversion ◽  
Data Interpretation ◽  
P Wave ◽  
S Wave ◽  
Southern France ◽  
Large N ◽  
Short Period

<p>Horizontal-to-Vertical Spectral Ratios (HVSR) and Rayleigh group velocity dispersion curves (DC) can be used to estimate the shallow S-wave velocity (Vs) structure. Knowing the shallow Vs structure is important for geophysical data interpretation either in order to better constrain data inversions for P-wave velocity (Vp) structures such as travel time tomography or full waveform inversions, or to directly study the Vs structure for geo-engineering purposes (e.g. ground motion prediction). The purpose of this study is to appraise in particular how much information HVSR can add in a large N experiment and how different instrumentation types affect this. </p><p>During the Maupasacq large-scale experiment, 197 three-component short-period stations, 190 geophone nodes and 54 broadband seismometers were continuously operated in Southern France for 6 months (April to October 2017) covering an area of approximately 1500 km2 with a site spacing of approximately 1 to 3 km. On the obtained HVSR and DC data, a statistical Joint inversion is performed for the shallow Vs structure. The results indicate that the addition of HVSR data to the DC inversion reduces the variance of the recovered shallow Vs model and improves the convergence to a smaller data misfit. While broadband and short period instruments delivered similar results, geophone nodes performed significantly worse due to their much higher cut off frequency. </p>

Passive seismic interferometry of the ultraslow-spreading Southwest Indian Ridge 

2021 ◽  
Author(s):  
Mohamadhasan Mohamadian Sarvandani ◽  
Emanuel Kästle ◽  
Lapo Boschi ◽  
Sylvie Leroy ◽  
Mathilde Cannat
Keyword(s):  
Wave Velocity ◽  
Vertical Component ◽  
Velocity Model ◽  
Southwest Indian Ridge ◽  
Seismic Interferometry ◽  
Ocean Bottom ◽  
S Wave ◽  
Passive Seismic ◽  
Indian Ridge ◽  
Marine Exploration

<p>Passive seismic interferometry (ambient-noise seismology) is an increasingly popular, eco-friendly, relatively inexpensive exploration geophysics tool, to map S-wave velocity in the Earth’s crust. This method has not yet been applied widely to marine exploration. The purpose of this study is to investigate the crustal structure of a quasi-amagmatic portion of the Southwest Indian Ridge by interferometry, and to examine the performance and reliability of interferometry in marine exploration. To achieve this goal, continuous vertical-component recordings from 43 ocean bottom seismometers (OBS) deployed during the SISMO-SMOOTH cruise (2014) were utilized. Recorded signals span frequencies between 0.1Hz and 3Hz. We show that reliable estimates of the Green’s function are obtained for many station pairs, by cross-correlation in the frequency domain. The comparison of the cross-correlations with the theoretical Green’s (Bessel) function provides one Rayleigh-wave dispersion curve per station pair; dispersion curves are then averaged, and inverted through a conditional neighborhood algorithm to determine a 1D S-wave velocity model, that we estimate to be well constrained within the crust. Our S-wave velocity model is analyzed and interpreted with geological information, and independent geophysical studies in the region of interest, as well as other areas characterized by similar tectonically-dominated, quasi amagmatic spreadings.</p>

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