scholarly journals Subsurface Imaging with Ocean‐Bottom Distributed Acoustic Sensing and Water Phases Reverberations

2022 ◽  
Author(s):  
Zack J. Spica ◽  
Jorge C. Castellanos ◽  
Loïc Viens ◽  
Kiwamu Nishida ◽  
Takeshi Akuhara ◽  
...  
Keyword(s):  
Ocean Bottom ◽  
Subsurface Imaging ◽  
Acoustic Sensing ◽  
Distributed Acoustic Sensing

Automatic Earthquake Detection and De-noising for Distributed Acoustic Sensing: Examples from On-land and Underwater Fibers

2020 ◽  
Author(s):  
Itzhak Lior ◽  
Daniel Mata ◽  
Gauthier Guerin ◽  
Diane Rivet ◽  
Anthony Sladen ◽  
...  
Keyword(s):  
Optical Fibers ◽  
Cross Correlation ◽  
Early Warning Systems ◽  
Earthquake Catalog ◽  
Ocean Bottom ◽  
Detection Scheme ◽  
Acoustic Sensing ◽  
Earthquake Detection ◽  
Waveform Similarity ◽  
Distributed Acoustic Sensing

<p>The use of underwater optical fibers, such as those currently traversing most of the world's oceans, for distributed acoustic sensing (DAS) holds great potential for seismic monitoring by complementing on-land seismic observations, especially near underwater faults. The analysis of underwater DAS records presents special challenges due to the noisy environment and the uneven cable-seafloor coupling. To fully exploit the potential of these records, automatically detecting and extracting seismic signals is imperative. To this end, a new automatic earthquake detection scheme is presented, based on waveform-similarity. Cross correlations between nearby records along the fiber are continuously calculated in short overlapping intervals. Earthquakes are detected as abrupt increases in cross correlation values over large segments of the cable. This procedure is applied to records of four existing fibers: one on land (Near Teil, south of France) and three underwater (one in Toulon, south of France, and two in Pylos, south-west Greece). Detected earthquakes are compared to earthquake catalogs and detection thresholds are obtained. That several of the detected earthquakes do not appear in any earthquake catalog demonstrates the proposed method's robustness. The cross correlation time shifts are then used to perform moveout corrections to the time series and phase weighted stacking (PWS) is applied to groups of neighboring traces. Unlike simple stacking approaches, PWS significantly enhances signal to noise ratios, allowing for more precise earthquake analysis and characterization. Further developing and applying such automatic techniques to ocean bottom fibers will enhance the performance of earthquake early warning systems, improving alert times for earthquakes occurring on underwater faults.</p>

scholarly journals Utilizing Distributed Acoustic Sensing and Ocean Bottom Fiber Optic Cables for Submarine Structural Characterization

2020 ◽  
Author(s):  
Feng Cheng ◽  
Jonathan Ajo-Franklin ◽  
Benxin Chi ◽  
Nathaniel J. Lindsey ◽  
Craig Dawe
Keyword(s):  
Structural Characterization ◽  
Fiber Optic ◽  
Ocean Bottom ◽  
Acoustic Sensing ◽  
Distributed Acoustic Sensing

scholarly journals Strain to ground motion conversion of distributed acoustic sensing data for earthquake magnitude and stress drop determination

Solid Earth ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 1421-1442
Author(s):  
Itzhak Lior ◽  
Anthony Sladen ◽  
Diego Mercerat ◽  
Jean-Paul Ampuero ◽  
Diane Rivet ◽  
...  
Keyword(s):  
Early Warning ◽  
Stress Drop ◽  
Source Parameters ◽  
Earthquake Early Warning ◽  
Body Waves ◽  
Ocean Bottom ◽  
Correlated Noise ◽  
Acoustic Sensing ◽  
Earthquake Source Parameters ◽  
Distributed Acoustic Sensing

Abstract. The use of distributed acoustic sensing (DAS) presents unique advantages for earthquake monitoring compared with standard seismic networks: spatially dense measurements adapted for harsh environments and designed for remote operation. However, the ability to determine earthquake source parameters using DAS is yet to be fully established. In particular, resolving the magnitude and stress drop is a fundamental objective for seismic monitoring and earthquake early warning. To apply existing methods for source parameter estimation to DAS signals, they must first be converted from strain to ground motions. This conversion can be achieved using the waves' apparent phase velocity, which varies for different seismic phases ranging from fast body waves to slow surface and scattered waves. To facilitate this conversion and improve its reliability, an algorithm for slowness determination is presented, based on the local slant-stack transform. This approach yields a unique slowness value at each time instance of a DAS time series. The ability to convert strain-rate signals to ground accelerations is validated using simulated data and applied to several earthquakes recorded by dark fibers of three ocean-bottom telecommunication cables in the Mediterranean Sea. The conversion emphasizes fast body waves compared to slow scattered waves and ambient noise and is robust even in the presence of correlated noise and varying wave propagation directions. Good agreement is found between source parameters determined using converted DAS waveforms and on-land seismometers for both P and S wave records. The demonstrated ability to resolve source parameters using P waves on horizontal ocean-bottom fibers is key for the implementation of DAS-based earthquake early warning, which will significantly improve hazard mitigation capabilities for offshore earthquakes, including those capable of generating tsunami.

Distributed Acoustic Sensing Turns Fiber‐Optic Cables into Sensitive Seismic Antennas

2019 ◽  
Vol 91 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Zhongwen Zhan
Keyword(s):  
Seismic Waves ◽  
Fiber Optic ◽  
Glass Fibers ◽  
Ocean Bottom ◽  
Thin Glass ◽  
Acoustic Sensing ◽  
Wide Range ◽  
Solar System Bodies ◽  
Distributed Acoustic Sensing ◽  
Seismic Networks

Abstract Distributed acoustic sensing (DAS) is a new, relatively inexpensive technology that is rapidly demonstrating its promise for recording earthquake waves and other seismic signals in a wide range of research and public safety arenas. It should significantly augment present seismic networks. For several important applications, it should be superior. It employs ordinary fiber‐optic cables, but not as channels for data among separate sophisticated instruments. With DAS, the hair‐thin glass fibers themselves are the sensors. Internal natural flaws serve as seismic strainmeters, kinds of seismic detector. Unused or dark fibers are common in fiber cables widespread around the globe, or in dedicated cables designed for special application, are appropriate for DAS. They can sample passing seismic waves at locations every few meters or closer along paths stretching for tens of kilometers. DAS arrays should enrich the three major areas of local and regional seismology: earthquake monitoring, imaging of faults and many other geologic formations, and hazard assessment. Recent laboratory and field results from DAS tests underscore its broad bandwidth and high‐waveform fidelity. Thus, while still in its infancy, DAS already has shown itself as the working heart—or perhaps ear drums—of a valuable new seismic listening tool. My colleagues and I expect rapid growth of applications. We further expect it to spread into such frontiers as ocean‐bottom seismology, glacial and related cryoseismology, and seismology on other solar system bodies.

scholarly journals Teleseisms and Microseisms on an Ocean-Bottom Distributed Acoustic Sensing Array

2019 ◽  
Author(s):  
Ethan Williams ◽  
Maria Fernandez-Ruiz ◽  
Regina Magalhaes ◽  
Roel Vanthillo ◽  
Zhongwen Zhan ◽  
...  
Keyword(s):  
Ocean Bottom ◽  
Acoustic Sensing ◽  
Distributed Acoustic Sensing

scholarly journals Utilizing distributed acoustic sensing and ocean bottom fiber optic cables for submarine structural characterization

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Feng Cheng ◽  
Benxin Chi ◽  
Nathaniel J. Lindsey ◽  
T. Craig Dawe ◽  
Jonathan B. Ajo-Franklin
Keyword(s):  
Structural Characterization ◽  
Ambient Noise ◽  
Fiber Optic ◽  
Monterey Bay ◽  
Ocean Bottom ◽  
Acoustic Sensing ◽  
Scholte Waves ◽  
Velocity Image ◽  
Distributed Acoustic Sensing ◽  
Marine Cable

AbstractThe sparsity of permanent seismic instrumentation in marine environments often limits the availability of subsea information on geohazards, including active fault systems, in both time and space. One sensing resource that provides observational access to the seafloor environment are existing networks of ocean bottom fiber optic cables; these cables, coupled to modern distributed acoustic sensing (DAS) systems, can provide dense arrays of broadband seismic observations capable of recording both seismic events and the ambient noise wavefield. Here, we report a marine DAS application which demonstrates the strength and limitation of this new technique on submarine structural characterization. Based on ambient noise DAS records on a 20 km section of a fiber optic cable offshore of Moss Landing, CA, in Monterey Bay, we extract Scholte waves from DAS ambient noise records using interferometry techniques and invert the resulting multimodal dispersion curves to recover a high resolution 2D shear-wave velocity image of the near seafloor sediments. We show for the first time that the migration of coherently scattered Scholte waves observed on DAS records can provide an approach for resolving sharp lateral contrasts in subsurface properties, particularly shallow faults and depositional features near the seafloor. Our results provide improved constraints on shallow submarine features in Monterey Bay, including fault zones and paleo-channel deposits, thus highlighting one of many possible geophysical uses of the marine cable network.

Detecting Leaks in Abandoned Gas Wells with Fibre-Optic Distributed Acoustic Sensing

2014 ◽  
Author(s):  
K. Boone ◽  
A. Ridge ◽  
R. Crickmore ◽  
D. Onen
Keyword(s):  
Fibre Optic ◽  
Gas Wells ◽  
Acoustic Sensing ◽  
Distributed Acoustic Sensing

scholarly journals Low‐Magnitude Seismicity With a Downhole Distributed Acoustic Sensing Array—Examples From the FORGE Geothermal Experiment

2020 ◽  
Vol 126 (1) ◽  
Author(s):  
A. Lellouch ◽  
R. Schultz ◽  
N.J. Lindsey ◽  
B.L. Biondi ◽  
W.L. Ellsworth
Keyword(s):  
Acoustic Sensing ◽  
Distributed Acoustic Sensing ◽  
Low Magnitude

Combining Distributed Acoustic Sensing and Beamforming in a Volcanic Environment on Mount Meager, British Columbia.

2021 ◽  
Author(s):  
Sara Klaasen ◽  
Patrick Paitz ◽  
Jan Dettmer ◽  
Andreas Fichtner
Keyword(s):  
British Columbia ◽  
Power Distribution ◽  
High Frequency ◽  
Low Frequency ◽  
Volcanic Tremor ◽  
Extreme Environment ◽  
Volcanic Complex ◽  
Acoustic Sensing ◽  
Distributed Acoustic Sensing ◽  
Volcanic Environment

<p>We present one of the first applications of Distributed Acoustic Sensing (DAS) in a volcanic environment. The goals are twofold: First, we want to examine the feasibility of DAS in such a remote and extreme environment, and second, we search for active volcanic signals of Mount Meager in British Columbia (Canada). </p><p>The Mount Meager massif is an active volcanic complex that is estimated to have the largest geothermal potential in Canada and caused its largest recorded landslide in 2010. We installed a 3-km long fibre-optic cable at 2000 m elevation that crosses the ridge of Mount Meager and traverses the uppermost part of a glacier, yielding continuous measurements from 19 September to 17 October 2019.</p><p>We identify ~30 low-frequency (0.01-1 Hz) and 3000 high-frequency (5-45 Hz) events. The low-frequency events are not correlated with microseismic ocean or atmospheric noise sources and volcanic tremor remains a plausible origin. The frequency-power distribution of the high-frequency events indicates a natural origin, and beamforming on these events reveals distinct event clusters, predominantly in the direction of the main peaks of the volcanic complex. Numerical examples show that we can apply conventional beamforming to the data, and that the results are improved by taking the signal-to-noise ratio of individual channels into account.</p><p>The increased data quantity of DAS can outweigh the limitations due to the lower quality of individual channels in these hazardous and remote environments. We conclude that DAS is a promising tool in this setting that warrants further development.</p>

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