Recognition of the Rayleigh wave disturbances in the signals from depth pressure transducers of ocean-bottom seismic stations

2012 ◽  
Vol 48 (9-10) ◽  
pp. 671-679 ◽  
Author(s):  
V. G. Getmanov ◽  
A. D. Gvishiani ◽  
K. Stroker ◽  
G. Mungov
Keyword(s):  
Rayleigh Wave ◽  
Ocean Bottom ◽  
Seismic Stations ◽  
Pressure Transducers ◽  
Wave Disturbances

scholarly journals Integration of onshore and offshore seismic arrays to study the seismicity of the Calabrian Region: a two steps automatic procedure for the identification of the best stations geometry

2014 ◽  
Vol 36 ◽  
pp. 69-75 ◽  
Author(s):  
A. D'Alessandro ◽  
I. Guerra ◽  
G. D'Anna ◽  
A. Gervasi ◽  
P. Harabaglia ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Network Optimization ◽  
A Priori ◽  
Second Step ◽  
Ocean Bottom ◽  
Broadband Seismometer ◽  
Seismic Stations ◽  
Seismic Arrays ◽  
Monitoring Campaign ◽  
Seismographic Network

Abstract. We plan to deploy in the Taranto Gulf some Ocean Bottom broadband Seismometer with Hydrophones. Our aim is to investigate the offshore seismicity of the Sibari Gulf. The seismographic network optimization consists in the identification of the optimal sites for the installation of the offshore stations, which is a crucial factor for the success of the monitoring campaign. In this paper, we propose a two steps automatic procedure for the identification of the best stations geometry. In the first step, based on the application of a set of a priori criteria, the suitable sites to host the ocean bottom seismic stations are identified. In the second step, the network improvement is evaluated for all the possible stations geometries by means of numerical simulation. The application of this procedure allows us to identify the best stations geometry to be achieved in the monitoring campaign.

Determination of New Zealand Ocean Bottom Seismometer Orientation via Rayleigh-Wave Polarization

2012 ◽  
Vol 83 (4) ◽  
pp. 704-713 ◽  
Author(s):  
J. C. Stachnik ◽  
A. F. Sheehan ◽  
D. W. Zietlow ◽  
Z. Yang ◽  
J. Collins ◽  
...  
Keyword(s):  
New Zealand ◽  
Rayleigh Wave ◽  
Ocean Bottom ◽  
Ocean Bottom Seismometer ◽  
Wave Polarization ◽  
Seismometer Orientation

Shear attenuation and anelastic mechanisms in the central Pacific upper mantle

2020 ◽  
Author(s):  
Zhitu Ma ◽  
Colleen Dalton ◽  
Joshua Russell ◽  
James Gaherty ◽  
Greg Hirth ◽  
...  
Keyword(s):  
Grain Boundary ◽  
Rayleigh Wave ◽  
Rayleigh Waves ◽  
Plane Waves ◽  
Shear Velocity ◽  
Grain Boundary Sliding ◽  
Absorption Peak ◽  
Ocean Bottom ◽  
Central Pacific ◽  
Transition Depth

<p>We determine the mantle attenuation (1/Q) structure beneath 70 Myr seafloor in the central Pacific. We use long-period (33-100 sec) Rayleigh waves recorded by the NoMelt array of broadband ocean-bottom seismometers. After the removal of tilt and compliance noise, we are able to measure Rayleigh wave phase and amplitude for 125 earthquakes. The compliance correction for ocean wave pressure on the seafloor is particularly important for improving signal-to-noise at periods longer than 55 sec. Attenuation and azimuthally anisotropic phase velocity in the study area are determined by approximating the wavefield as the interference of two plane waves. We find that the amplitude decay of Rayleigh waves across the NoMelt array can be adequately explained using a two-layer model: in the shallow layer, in the deeper layer, and a transition depth at 70 km, although the sharpness of the transition is not well resolved by the Rayleigh wave data. Notably, observed in the NoMelt lithosphere is significantly higher than values in this area from global attenuation models. When compared with lithospheric measured at higher frequency (~3 Hz), the frequency dependence of attenuation is very slight, revising previous interpretations. The effect of anelasticity on shear velocity (V<sub>S</sub>) is estimated from the ratio of observed velocity to the predicted anharmonic value. We use laboratory-based parameters to predict attenuation and velocity-dispersion spectra that result from the superposition of a weakly frequency dependent high-temperature background and an absorption peak. We test a large range of frequencies for the position of the absorption peak (<em>f</em><sub>e</sub>) and determine, at each depth, which values of <em>f</em><sub>e</sub> predict and V<sub>S</sub> that can fit the NoMelt and V<sub>S </sub>values simultaneously. We show that between depths of 60 and 80 km the seismic models require an increase in <em>f</em><sub>e</sub> by at least 3-4 orders of magnitude. Under the assumption that the absorption peak is caused by elastically accommodated grain-boundary sliding, this increase in <em>f</em><sub>e</sub> reflects a decrease in grain-boundary viscosity of 3-4 orders of magnitude. A likely explanation is an increase in the water content of the mantle, with the base of the dehydrated lid located at ~70-km depth.   </p>

Estimations of Sensor Misorientation for Broadband Seismic Stations in and around Africa

2019 ◽  
Vol 90 (6) ◽  
pp. 2188-2204 ◽  
Author(s):  
Adebayo Oluwaseun Ojo ◽  
Li Zhao ◽  
Xin Wang
Keyword(s):  
Rayleigh Wave ◽  
Correlation Coefficients ◽  
Principal Component ◽  
Transverse Component ◽  
P Wave ◽  
Estimation Methods ◽  
Seismic Stations ◽  
Sensor Orientation ◽  
High Consistency ◽  
Misorientation Angles

ABSTRACT To ensure the accuracy of future seismological studies using horizontal‐component data recorded by broadband seismic stations in Africa and environs, we investigate the sensor orientation of 1075 stations belonging to 41 seismic networks deployed in and around the African continent in the past three decades. We applied three independent waveform‐based orientation estimation methods that involve the measurement of P‐wave particle motion based on the principal component analysis, minimizing the P‐wave energy on the transverse component of motion, and measuring intermediate‐period Rayleigh‐wave arrival angles from teleseismic earthquakes. We found that 34.3%–43.5% of the stations are well oriented within 3°, 40%–48.2% have sensor misorientation values between 3° and 10°, whereas 16.5%–18% of the stations are misaligned by more than 10°, most likely true sensor misorientation. The fairly high correlation coefficients (0.71–0.93) and very small mean (−0.01°–0.06°) and median (−0.04°–0.3°) differences suggest a high consistency among the estimates from the three methods. Likewise, the comparison of our results with reported orientations in the metadata at 33 stations demonstrates the robustness of the results obtained in this study. Likewise, the increase in the cross‐correlation coefficients and reduced time shifts between the Rayleigh‐wave signals on the vertical and Hilbert‐transformed radial components when the sensor misorientation angles are corrected show the importance of this study. An investigation of the time dependence of the estimated misorientation angles over the validation period reveals that the sensor orientation remained fairly constant for most stations included in the study. The nearly 180° sensor misorientation angles obtained at some stations led to the suspicion of possible polarity reversal of the seismometer components and/or channel mislabeling that was confirmed with a network manager for two of the seismic stations. Result of this study serves as a reference for future data users and a reminder to seismic network managers to decrease the number of errors that may lead to misorientations in future deployments.

Benchmarking Automated Rayleigh-Wave Arrival Angle Measurements for USArray Seismograms

2021 ◽  
Author(s):  
William D. Frazer ◽  
Adrian K. Doran ◽  
Gabi Laske
Keyword(s):  
Rayleigh Wave ◽  
3D Structure ◽  
Free Fall ◽  
Ocean Bottom ◽  
High Quality ◽  
Arrival Angle ◽  
Geographic Coordinate System ◽  
Seismic Networks ◽  
Arrival Angles ◽  
Wave Arrival

Abstract Surface-wave arrival angles are an important secondary set of observables to constrain Earth’s 3D structure. These data have also been used to refine information on the alignments of horizontal seismometer components with the geographic coordinate system. In the past, particle motion has been inspected and analyzed on single three-component seismograms, one at a time. But the advent of large, dense seismic networks has made this approach tedious and impractical. Automated toolboxes are now routinely used for datasets in which station operators cannot determine the orientation of a seismometer upon deployment, such as conventional free-fall ocean bottom seismometers. In a previous paper, we demonstrated that our automated Python-based toolbox Doran–Laske-Orientation-Python compares favorably with traditional approaches to determine instrument orientations. But an open question has been whether the technique also provides individual high-quality measurements for an internally consistent dataset to be used for structural imaging. For this feasibility study, we compared long-period Rayleigh-wave arrival angles at frequencies between 10 and 25 mHz for 10 earthquakes during the first half of 2009 that were recorded at the USArray Transportable Array—a component of the EarthScope program. After vigorous data vetting, we obtained a high-quality dataset that compares favorably with an arrival angle database compiled using our traditional interactive screen approach, particularly at frequencies 20 mHz and above. On the other hand, the presence of strong Love waves may hamper the automated measurement process as currently implemented.

scholarly journals Estimating the Rayleigh-wave impulse response between seismic stations with the cross terms of the Green tensor

2011 ◽  
Vol 38 (16) ◽  
pp. n/a-n/a ◽  
Author(s):  
Kasper van Wijk ◽  
T. Dylan Mikesell ◽  
Vera Schulte-Pelkum ◽  
Josh Stachnik
Keyword(s):  
Rayleigh Wave ◽  
Impulse Response ◽  
Green Tensor ◽  
Seismic Stations ◽  
Cross Terms ◽  
The Cross
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