scholarly journals Report on Cruise 2010007PGC, C.C.G. Vessel John P. Tully, 30 June - 10 July 2010, SeaJade-I Seafloor Earthquake Array - Japan Canada Cascadia Experiment, Ocean bottom seismometer recovery, methane gas-plume acoustic imaging, and CTD-water sampling program

2014 ◽  
Author(s):  
M Riedel ◽  
M M Côté ◽  
P J Neelands ◽  
K Obana ◽  
R Wania ◽  
...  
Keyword(s):  
Acoustic Imaging ◽  
Ocean Bottom ◽  
Ocean Bottom Seismometer ◽  
Water Sampling ◽  
Methane Gas ◽  
Sampling Program

Comparison of the S/N ratios of low-frequency hydrophones and geophones as a function of ocean depth

1981 ◽  
Vol 71 (5) ◽  
pp. 1649-1659
Author(s):  
Thomas M. Brocher ◽  
Brian T. Iwatake ◽  
Joseph F. Gettrust ◽  
George H. Sutton ◽  
L. Neil Frazer
Keyword(s):  
Nova Scotia ◽  
Continental Margin ◽  
Low Frequency ◽  
Weather Conditions ◽  
Ocean Bottom ◽  
Ocean Bottom Seismometer ◽  
Scotian Shelf ◽  
Ocean Bottom Seismometers ◽  
Particle Velocities ◽  
Refraction Data

abstract The pressures and particle velocities of sediment-borne signals were recorded over a 9-day period by an array of telemetered ocean-bottom seismometers positioned on the continental margin off Nova Scotia. The telemetered ocean-bottom seismometer packages, which appear to have been very well coupled to the sediments, contained three orthogonal geophones and a hydrophone. The bandwidth of all sensors was 1 to 30 Hz. Analysis of the refraction data shows that the vertical geophones have the best S/N ratio for the sediment-borne signals at all recording depths (67, 140, and 1301 m) and nearly all ranges. The S/N ratio increases with increasing sensor depth for equivalent weather conditions. Stoneley and Love waves detected on the Scotian shelf (67-m depth) are efficient modes for the propagation of noise.

An ocean-bottom seismometer capsule

1974 ◽  
Vol 64 (4) ◽  
pp. 1251-1262
Author(s):  
William A. Prothero
Keyword(s):  
Seismic Event ◽  
Field Tests ◽  
Data Interpretation ◽  
Seismic Signal ◽  
Digital Data ◽  
Ocean Bottom ◽  
Ocean Bottom Seismometer ◽  
Event Trigger ◽  
Analog Output ◽  
Predetermined Time

abstract An ocean-bottom seismometer capsule containing a 1-Hz vertical seismometer and triggered digital recording system has been developed and tested off the coast of San Diego. The output of the seismometer is continuously digitized at 64, 128, or 256 samples per second. The digital data is mixed with a time code and passed through a 256 sample shift register which acts as a delay line. It is then mixed with synchronization characters, serialized, encoded, and recorded on a SONY TC800B tape recorder which is turned on when a seismic event occurs. The event trigger occurs when the seismic signal jumps to at least twice the time-averaged input signal. Data are recovered using the same recorder for playback and a decoder which provides an analog output for field data interpretation or a digital output for computer analysis. The capsule itself falls freely to the ocean bottom. After a predetermined time it is released from a 150-lb steel tripod and floats to the surface. A dual timer and explosive bolt system provides a high recovery reliability. A number of seismic events have been measured in field tests and the system has proven to be extremely simple to check out, diagnose, and deploy.

Seismically Derived Ground Tilts Related to the 2010 Chilean Tsunami

2021 ◽  
Author(s):  
Jui-Chun Freya Chen ◽  
Wu-Cheng Chi ◽  
Chu-Fang Yang
Keyword(s):  
Deep Ocean ◽  
Propagation Model ◽  
Ocean Bottom ◽  
Ocean Bottom Seismometer ◽  
Tsunami Propagation ◽  
Ground Tilt ◽  
Tsunami Waves ◽  
The Pacific ◽  
Seismic Networks ◽  
Back Azimuth

Abstract Developing new ways to observe tsunami contributes to tsunami research. Tidal and deep-ocean gauges are typically used for coastal and offshore observations. Recently, tsunami-induced ground tilts offer a new possibility. The ground tilt signal accompanied by 2010 Mw 8.8 Chilean earthquake were observed at a tiltmeter network in Japan. However, tiltmeter stations are usually not as widely installed as broadband seismometers in other countries. Here, we studied broadband seismic records from Japan’s F-net and found ground tilt signals consistent with previously published tiltmeter dataset for this particular tsunamic event. Similar waveforms can also be found in broadband seismic networks in other countries, such as Taiwan, as well as an ocean-bottom seismometer. We documented a consistent time sequence of evolving back-azimuth directions of the tsunami waves at different stages of tsunami propagation through beamforming-frequency–wavenumber analysis and particle-motion analysis; the outcomes are consistent with the tsunami propagation model provided by the Pacific Tsunami Warning Center. These results shown that dense broadband seismic networks can provide a useful complementary dataset, in addition to tiltmeter arrays and other networks, to study or even monitor tsunami propagation using arrayed methods.

scholarly journals Exploring the submarine Graham Bank in the Sicily Channel

2016 ◽  
Vol 59 (2) ◽  
Author(s):  
Mauro Coltelli ◽  
Danilo Cavallaro ◽  
Giuseppe D’Anna ◽  
Antonino D’Alessandro ◽  
Fausto Grassa ◽  
...  
Keyword(s):  
Volcanic Activity ◽  
Structural Features ◽  
Ocean Bottom ◽  
Ocean Bottom Seismometer ◽  
Remotely Operated Vehicle ◽  
Bathymetric Survey ◽  
Submarine Volcanism ◽  
Historical Times ◽  
Sicily Channel ◽  
Sonar Echoes

<p>In the Sicily Channel, volcanic activity has been concentrated mainly on the Pantelleria and Linosa islands, while minor submarine volcanism took place in the Adventure, Graham and Nameless banks. The volcanic activity spanned mostly during Plio-Pleistocene, however, historical submarine eruptions occurred in 1831 on the Graham Bank and in 1891 offshore Pantelleria Island. On the Graham Bank, 25 miles SW of Sciacca, the 1831 eruption formed the short-lived Ferdinandea Island that represents the only Italian volcano active in historical times currently almost completely unknown and not yet monitored. Moreover, most of the Sicily Channel seismicity is concentrated along a broad NS belt extending from the Graham Bank to Lampedusa Island. In 2012, the Istituto Nazionale di Geofisica e Vulcanologia (INGV) carried out a multidisciplinary oceanographic cruise, named “Ferdinandea 2012”, the preliminary results of which represent the aim of this paper. The cruise goal was the mapping of the morpho-structural features of some submarine volcanic centres located in the northwestern side of the Sicily Channel and the temporary recording of their seismic and degassing activity. During the cruise, three OBS/Hs (ocean bottom seismometer with hydrophone) were deployed near the Graham, Nerita and Terribile submarine banks. During the following 9 months they have recorded several seismo-acoustic signals produced by both tectonic and volcanic sources. A high-resolution bathymetric survey was achieved on the Graham Bank and on the surrounding submarine volcanic centres. A widespread and voluminous gas bubbles emission was observed by both multibeam sonar echoes and a ROV (remotely operated vehicle) along the NW side of the Graham Bank, where gas and seafloor samples were also collected.</p>

Seismic structure of the extended continental crust in the Yamato Basin, Japan Sea, from ocean bottom seismometer survey

2013 ◽  
Vol 67-68 ◽  
pp. 199-206 ◽  
Author(s):  
Kazuo Nakahigashi ◽  
Masanao Shinohara ◽  
Tomoaki Yamada ◽  
Kenji Uehira ◽  
Kimihiro Mochizuki ◽  
...  
Keyword(s):  
Continental Crust ◽  
Japan Sea ◽  
Ocean Bottom ◽  
Ocean Bottom Seismometer ◽  
Seismic Structure ◽  
Yamato Basin

Characteristics of Current-Induced Harmonic Tremor Signals in Ocean-Bottom Seismometer Records

2021 ◽  
Author(s):  
David Essing ◽  
Vera Schlindwein ◽  
Mechita C. Schmidt-Aursch ◽  
Celine Hadziioannou ◽  
Simon C. Stähler
Keyword(s):  
Time Series ◽  
Fundamental Frequency ◽  
Volcanic Tremor ◽  
Mode Locking ◽  
Spectral Amplitude ◽  
Bottom Current ◽  
Ocean Bottom ◽  
Ocean Bottom Seismometer ◽  
Natural Sources ◽  
Bottom Currents

Abstract Long-lasting harmonic tremor signals are frequently observed in spectrograms of seismological data. Natural sources, such as volcanoes and icebergs, or artificial sources, such as ships and helicopters, produce very similar harmonic tremor episodes. Ocean-bottom seismometer (OBS) records may additionally be contaminated by tremor induced by ocean-bottom currents acting on the OBS structure. This harmonic tremor noise may severely hinder earthquake detection and can be misinterpreted as volcanic tremor. In a 160-km-long network of 27 OBSs deployed for 1 yr along the Knipovich ridge in the Greenland Sea, harmonic tremor was widely observed away from natural sources such as volcanoes. Based on this network, we present a systematic analysis of the characteristics of hydrodynamically induced harmonic tremor in OBS records to make it distinguishable from natural tremor sources and reveal its generation processes. We apply an algorithm that detects harmonic tremor and extracts time series of its fundamental frequency and spectral amplitude. Tremor episodes typically occur twice per day, starting with fundamental frequencies of 0.5–1.0 Hz, and show three distinct stages that are characterized by frequency-gliding, mode-locking, and large spectral amplitudes, respectively. We propose that ocean-bottom currents larger than ∼5  cm/s cause rhythmical Karman vortex shedding around protruding structures of the OBS and excite eigenvibrations. Head-buoy strumming is the most likely source of the dominant tremor signal, whereas a distinctly different tremor signal with a fundamental frequency ∼6  Hz may be related to eigenvibrations of the radio antenna. Ocean-bottom current velocities reconstructed from the fundamental tremor frequency and from cross correlation of tremor time series between stations match observed average current velocities of 14–20  cm/s in this region. The tremor signal periodicity shows the same tidal constituents as the forcing ocean-bottom currents, which is a further evidence of the hydrodynamic nature of the tremor.

Multi-parameter model building for the Qiuyue structure using four-component ocean-bottom seismometer data

Geophysics ◽  
2021 ◽  
pp. 1-52
Author(s):  
Yuzhu Liu ◽  
Xinquan Huang ◽  
Jizhong Yang ◽  
Xueyi Liu ◽  
Bin Li ◽  
...  
Keyword(s):  
Wave Velocity ◽  
Waveform Inversion ◽  
Velocity Model ◽  
P Wave ◽  
Velocity Analysis ◽  
Full Waveform Inversion ◽  
Ocean Bottom ◽  
Ocean Bottom Seismometer ◽  
Full Waveform ◽  
P Wave Velocity

Thin sand-mud-coal interbedded layers and multiples caused by shallow water pose great challenges to conventional 3D multi-channel seismic techniques used to detect the deeply buried reservoirs in the Qiuyue field. In 2017, a dense ocean-bottom seismometer (OBS) acquisition program acquired a four-component dataset in East China Sea. To delineate the deep reservoir structures in the Qiuyue field, we applied a full-waveform inversion (FWI) workflow to this dense four-component OBS dataset. After preprocessing, including receiver geometry correction, moveout correction, component rotation, and energy transformation from 3D to 2D, a preconditioned first-arrival traveltime tomography based on an improved scattering integral algorithm is applied to construct an initial P-wave velocity model. To eliminate the influence of the wavelet estimation process, a convolutional-wavefield-based objective function for the preprocessed hydrophone component is used during acoustic FWI. By inverting the waveforms associated with early arrivals, a relatively high-resolution underground P-wave velocity model is obtained, with updates at 2.0 km and 4.7 km depth. Initial S-wave velocity and density models are then constructed based on their prior relationships to the P-wave velocity, accompanied by a reciprocal source-independent elastic full-waveform inversion to refine both velocity models. Compared to a traditional workflow, guided by stacking velocity analysis or migration velocity analysis, and using only the pressure component or other single-component, the workflow presented in this study represents a good approach for inverting the four-component OBS dataset to characterize sub-seafloor velocity structures.

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