Very low frequency Ocean Bottom ambient seismic noise and coupling on the shallow continental shelf

1989 ◽  
Vol 11 (2) ◽  
pp. 129-152 ◽  
Author(s):  
Mark V. Trevorrow ◽  
Tokuo Yamamoto ◽  
Altan Turgut ◽  
Dean Goodman ◽  
Mohsen Badiey
Keyword(s):  
Continental Shelf ◽  
Seismic Noise ◽  
Low Frequency ◽  
Ambient Seismic Noise ◽  
Ocean Bottom ◽  
Very Low Frequency

Ambient seismic noise suppression in COST action G2Net

2020 ◽  
Author(s):  
Velimir Ilić ◽  
Alessandro Bertolini ◽  
Fabio Bonsignorio ◽  
Dario Jozinović ◽  
Tomasz Bulik ◽  
...  
Keyword(s):  
Machine Learning ◽  
Gravitational Waves ◽  
Seismic Noise ◽  
Noise Suppression ◽  
Real Life ◽  
Low Frequency ◽  
Ambient Seismic Noise ◽  
Cost Action ◽  
The Cost ◽  
Life Challenge

<p>The analysis of low-frequency gravitational waves (GW) data is a crucial mission of GW science and the performance of Earth-based GW detectors is largely influenced by ability of combating the low-frequency ambient seismic noise and other seismic influences. This tasks require multidisciplinary research in the fields of seismic sensing, signal processing, robotics, machine learning and mathematical modeling.<br><br>In practice, this kind of research is conducted by large teams of researchers with different expertise, so that project management emerges as an important real life challenge in the projects for acquisition, processing and interpretation of seismic data from GW detector site. A prominent example that successfully deals with this aspect could be observed in the COST Action G2Net (CA17137 - A network for Gravitational Waves, Geophysics and Machine Learning) and its seismic research group, which counts more than 30 members. </p><div>In this talk we will review the structure of the group, present the goals and recent activities of the group, and present new methods for combating the seismic influences at GW detector site that will be developed and applied within this collaboration.</div><div> <p> </p> <p>This publication is based upon work from CA17137 - A network for Gravitational Waves, Geophysics and Machine Learning, supported by COST (European Cooperation in Science and Technology).</p> </div>

Low-Frequency Tremors Immediately After the 2011 Tohoku-Oki Earthquake Detected by Near-Trench OBS Observations

2020 ◽  
Author(s):  
Hidenobu Takahashi ◽  
Ryota Hino ◽  
Naoki Uchida ◽  
Takanori Matsuzawa ◽  
Yusaku Ohta ◽  
...  
Keyword(s):  
Near Field ◽  
Low Frequency ◽  
Spectral Shape ◽  
Ocean Bottom ◽  
Aseismic Slip ◽  
Very Low Frequency ◽  
Repeating Earthquakes ◽  
Ocean Bottom Seismometers ◽  
Repeating Earthquake ◽  
Interplate Earthquakes

Abstract We used temporal seismic observation using pop-up type ocean-bottom seismometers to detect a number of low-frequency tremors (LFTs) immediately after the 2011 Tohoku-Oki earthquake in the northern periphery of its aftershock area. The near-field observation clearly distinguished LFTs from regular earthquakes based on their spectral shape in the frequency band of 1–4 Hz. In addition to the LFTs accompanied by known very low frequency earthquakes (VLFEs), more than 130 LFTs without known VLFE activity were detected during April–October, 2011. The newly detected LFTs were in the vicinity of a sequence of small repeating earthquakes indicating mixed distribution of LFTs and regular interplate earthquakes in the region. The LFTs and repeating earthquake activities show a periodicity of 60–100 days, which is similar to that of the LFT activity in the later period (2016–2018). This suggests that the LFT activity is modulated by sustained background aseismic slip events throughout the postseismic period of the 2011 mainshock.

Correction of Ocean-Bottom Seismometer Instrumental Clock Errors Using Ambient Seismic Noise

2014 ◽  
Vol 104 (3) ◽  
pp. 1276-1288 ◽  
Author(s):  
P. Gouedard ◽  
T. Seher ◽  
J. J. McGuire ◽  
J. A. Collins ◽  
R. D. van der Hilst
Keyword(s):  
Seismic Noise ◽  
Ambient Seismic Noise ◽  
Ocean Bottom ◽  
Ocean Bottom Seismometer

Sources of primary and secondary microseisms

1994 ◽  
Vol 84 (1) ◽  
pp. 142-148
Author(s):  
Robert K. Cessaro
Keyword(s):  
Seismic Noise ◽  
Low Frequency ◽  
Seismic Array ◽  
Wave Number ◽  
Ocean Bottom ◽  
Wide Angle ◽  
Frequency Wave ◽  
Long Period ◽  
Seismic Records ◽  
Near Shore

Abstract Low-frequency (0.01 to 0.2 Hz) seismic noise, arising from pelagic storms, is commonly observed as microseisms in seismic records from land and ocean bottom detectors. One principal research objective, in the study of microseisms, has been to locate their sources. This article reports on an analysis of primary and secondary microseisms (i.e., near and double the frequency of ocean swell) recorded simultaneously on three land-based long-period arrays (Alaskan Long Period Array, Montana Large Aperture Seismic Array, and Norwegian Seismic Array) during the early 1970s. Reliable microseism source locations are determined by wide-angle triangulation, using the azimuths of approach obtained from frequency-wave number analysis of the records of microseisms propagating across these arrays. Two near-shore sources of both primary and secondary microseisms appear to be persistent in the sense that they are associated with essentially constant near-shore locations. Secondary microseisms are observed to emanate from wide-ranging pelagic locations in addition to the same near-shore locations determined for the primary microseisms.

Extracting subsurface information from ambient seismic noise — A case study from Germany

Geophysics ◽  
2012 ◽  
Vol 77 (4) ◽  
pp. KS13-KS31 ◽  
Author(s):  
Alexander Goertz ◽  
Barbara Schechinger ◽  
Benjamin Witten ◽  
Matthias Koerbe ◽  
Paul Krajewski
Keyword(s):  
Seismic Noise ◽  
Body Wave ◽  
Source Region ◽  
Low Frequency ◽  
Spectral Ratio ◽  
Velocity Model ◽  
Body Waves ◽  
Seismic Survey ◽  
Ambient Seismic Noise ◽  
Oil Reservoir

We analyzed ambient seismic noise from a broadband passive seismic survey acquired in an urban area in Germany. Despite a high level of anthropogenic noise, we observe lateral variations in the quasi-stationary spectra that are of natural origin and indicative of the subsurface in the survey area. The best diagnostic is the ellipticity spectrum which is the spectral ratio of the vertical over the horizontal components. Deviations of the observed spectra from a pure Rayleigh-wave ellipticity allow an approximate separation of surface-wave from body-wave components in the analyzed frequency range, distinguishing shallow (upper tens of meters) from deeper (upper three kilometers) subsurface effects. We observe an increase of vertically polarized body waves between 1 and 4 Hz that is correlated to a subsurface structure that contains an oil reservoir at about 2-km depth. We located the source of the observed body wave microtremor in depth by applying an elastic wavefield back projection and imaging technique. The method includes normalization by the impulse response of the velocity model, effects of the receiver geometry, and lateral variation of incoherent noise. The source region of the low-frequency body wave microtremor is centered above the location of the oil reservoir. Two possible explanations for the deep microtremor are elastic body-wave scattering due to the impedance contrast of the structural trap, and viscoelastic scattering due to poroelastic effects in the partially saturated reservoir.

scholarly journals Determining OBS clock drift using ambient seismic noise 

2021 ◽  
Author(s):  
David Naranjo ◽  
Laura Parisi ◽  
Philippe Jousset ◽  
Cornelis Weemstra ◽  
Sigurjón Jónsson
Keyword(s):  
Seismic Noise ◽  
Temperature Drop ◽  
Time Lapse ◽  
Ambient Seismic Noise ◽  
Ocean Bottom ◽  
Timing Error ◽  
Clock Drift ◽  
Ocean Bottom Seismometers ◽  
Cross Correlations ◽  
Reykjanes Peninsula

<p>Accurate timing of seismic records is essential for almost all applications in seismology. Wrong timing of the waveforms may result in incorrect Earth models and/or inaccurate earthquake locations. As such, it may render interpretations of underground processes incorrect. Ocean bottom seismometers (OBSs) experience clock drifts due to their inability to synchronize with a GNSS signal (with the correct reference time), since electromagnetic signals are unable to propagate efficiently in water. As OBSs generally operate in relatively stable ambient temperature, the timing deviation is usually assumed to be linear. Therefore, the time corrections can be estimated through GPS synchronization before deployment and after recovery of the instrument. However, if the instrument has run out of power prior to recovery (i.e., due to the battery being dead at the time of recovery), the timing error at the end of the deployment cannot be determined. In addition, the drift may not be linear, e.g., due to rapid temperature drop while the OBS sinks to the seabed. Here we present an algorithm that recovers the linear clock drift, as well as a potential timing error at the onset.</p><p>The algorithm presented in this study exploits seismic interferometry (SI). Specifically, time-lapse (averaged) cross-correlations of ambient seismic noise are computed. As such, virtual-source responses, which are generally dominated by the recorded surface waves, are retrieved. These interferometric responses generate two virtual sources: a causal wave (arriving at a positive time) and an acausal wave (arriving at a negative time). Under favorable conditions, both interferometric responses approach the surface-wave part of the medium's Green's function. Therefore, it is possible to calculate the clock drift for each station by exploiting the time-symmetry between the causal and acausal waves. For this purpose, the clock drift is calculated by measuring the differential arrival times of the causal and acausal waves for a large number of receiver-receiver pairs and computing the drift by carrying-out a least-squares inversion. The methodology described is applied to time-lapse cross-correlations of ambient seismic noise recorded on and around the Reykjanes peninsula, SW Iceland. The stations used for the analysis were deployed in the context of IMAGE (Integrated Methods for Advanced Geothermal Exploration) and consisted of 30 on-land stations and 24 ocean bottom seismometers (OBSs).  The seismic activity was recorded from spring 2014 until August 2015 on an area of around 100 km in diameter (from the tip of the Reykjanes peninsula).</p>

scholarly journals Characteristics of Low-frequency Ambient Seismic Noise in South Korea

2016 ◽  
Vol 19 (2) ◽  
pp. 67-75
Author(s):  
Iseul Park ◽  
Ki Young Kim ◽  
Joongmoo Byu
Keyword(s):  
South Korea ◽  
Seismic Noise ◽  
Low Frequency ◽  
Ambient Seismic Noise
Sign in / Sign up

Export Citation Format

Share Document