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

High resolution seafloor thermometry for internal wave and upwelling monitoring using Distributed Acoustic Sensing

Temperature is an essential oceanographic variable (EOV) that still today remains coarsely resolved below the surface and near the seafloor. Here, we gather evidence to confirm that Distributed Acoustic Sensing (DAS) technology can convert tens of kilometer-long seafloor fiber-optic telecommunication cables into dense arrays of temperature anomaly sensors having millikelvin (mK) sensitivity, thus allowing to monitor oceanic processes such as internal waves and upwelling with unprecedented detail. Notably, we report high-resolution observations of highly coherent near-inertial and super-inertial internal waves in the NW Mediterranean sea, offshore of Toulon, France, having spatial extents of a few kilometers and producing maximum thermal anomalies of more than 5 K at maximum absolute rates of more than 1 K/h. We validate our observations with in-situ oceanographic sensors and an alternative optical fiber sensing technology. Currently, DAS only provides temperature changes estimates, however practical solutions are outlined to obtain continuous absolute temperature measurements with DAS at the seafloor. Our observations grant key advantages to DAS over established temperature sensors, showing its transformative potential for the description of seafloor temperature fluctuations over an extended range of spatial and temporal scales, as well as for the understanding of the evolution of the ocean in a broad sense (e.g. physical and ecological). Diverse ocean-oriented fields could benefit from the potential applications of this fast-developing technology.

Principles and Applications of Seismic Monitoring Based on Submarine Optical Cable

Submarine optical cables, utilized as fiber-optic sensors for seismic monitoring, are gaining increasing interest because of their advantages of extending the detection coverage, improving the detection quality, and enhancing long-term stability. The fiber-optic seismic monitoring sensors are mainly composed of the optical interferometer, fiber Bragg grating, optical polarimeter, and distributed acoustic sensing, respectively. This paper reviews the principles of the four optical seismic sensors, as well as their applications of submarine seismology over submarine optical cables. The advantages and disadvantages are discussed, and the current technical requirements are concluded, respectively. This review can provide a reference for studying submarine cable-based seismic monitoring.

Seismic detection with distributed acoustic sensors using a convolutional neural network in the frequency wavenumber spectrum

With the development of optical fiber distributed acoustic sensors (DAS), their application to seismic observation has become popular. We conducted DAS measurements from November 19 to December 2, 2019, using dark fiber of an ocean bottom cable seismic and tsunami observation system off the Sanriku coast in northeastern Japan and investigated seismic detection methods from the obtained strain rate data. We examined a new seismic detection method using a convolutional neural network, to the best of our knowledge, treating a frequency wavenumber spectrum of strain rate as an image. This method effectively captured a characteristic wave described as the T-phase in a sound fixing and ranging channel even with low signal-to-noise ratio data.

Filtering Strategies for Deformation-Rate Distributed Acoustic Sensing

Deformation-rate distributed acoustic sensing (DAS), made available by the unique designs of certain interrogator units, acquires seismic data that are theoretically equivalent to the along-fiber particle velocity motion recorded by geophones for scenarios involving elastic ground-fiber coupling. While near-elastic coupling can be achieved in cemented downhole installations, it is less obvious how to do so in lower-cost horizontal deployments. This investigation addresses this challenge by installing and freezing fiber in shallow backfilled trenches (to 0.1 m depth) to achieve improved coupling. This acquisition allows for a reinterpretation of processed deformation-rate DAS waveforms as a "filtered particle velocity" rather than the conventional strain-rate quantity. We present 1D and 2D filtering experiments that suggest 2D velocity-dip filtering can recover improved DAS data panels that exhibit clear surface and refracted arrivals. Data acquired on DAS fibers deployed in backfilled, frozen trenches were more repeatable over a day of acquisition compared to those acquired on a surface-deployed DAS fiber, which exhibited more significant amplitude variations and lower signal-to-noise ratios. These observations suggest that deploying fiber in backfilled, frozen trenches can help limit the impact of environmental factors that would adversely affect interpretations of time-lapse DAS observations.

Sensitive seismic sensors based on microwave frequency fiber interferometry in commercially deployed cables

The use of fiber infrastructures for environmental sensing is attracting global interest, as optical fibers emerge as low cost and easily accessible platforms exhibiting a large terrestrial deployment. Moreover, optical fiber networks offer the unique advantage of providing observations of submarine areas, where the sparse existence of permanent seismic instrumentation due to cost and difficulties in deployment limits the availability of high-resolution subsea information on natural hazards in both time and space. The use of optical techniques that leverage pre-existing fiber infrastructure can efficiently provide higher resolution coverage and pave the way for the identification of the detailed structure of the Earth especially on seismogenic submarine faults. The prevailing optical technique for use in earthquake detection and structural analysis is distributed acoustic sensing (DAS) which offers high spatial resolution and sensitivity, however is limited in range (< 100 km). In this work, we present a novel technique which relies on the dissemination of a stable microwave frequency along optical fibers in a closed loop configuration, thereby forming an interferometer that is sensitive to deformation. We call the proposed technique Microwave Frequency Fiber Interferometer (MFFI) and demonstrate its sensitivity to deformation induced by moderate-to-large earthquakes from either local or regional epicenters. MFFI signals are compared to signals recorded by accelerometers of the National Observatory of Athens, Institute of Geodynamics National Seismic Network and by a commercially available DAS interrogator operating in parallel at the same location. Remarkable agreement in dynamical behavior and strain rate estimation is achieved and demonstrated. Thus, MFFI emerges as a novel technique in the field of fiber seismometers offering critical advantages with respect to implementation cost, maximum range and simplicity.

Distributed acoustic sensing for active offshore shear wave profiling

The long-term sustainability of the offshore wind industry requires the development of appropriate investigative methods to enable less conservative and more cost-effective geotechnical engineering design. Here we describe the novel use of distributed acoustic sensing (DAS) as part of an integrated approach for the geophysical and geotechnical assessment of the shallow subsurface for offshore construction. DAS was used to acquire active Scholte-wave seismic data at several locations in the vicinity of a planned windfarm development near Dundalk Bay, Irish Sea. Complimentary additional datasets include high-resolution sparker seismic reflection, cone penetration test (CPT) data and gravity coring. In terms of fibre optic cable selection, a CST armoured cable provided a reasonable compromise between performance and reliability in the offshore environment. Also, when used as a seismic source, a gravity corer enabled the fundamental mode Scholte-wave to be better resolved than an airgun, and may be more suitable in environmentally sensitive areas. Overall, the DAS approach was found to be effective at rapidly determining shear wave velocity profiles in areas of differing geological context, with metre scale spatial sampling, over multi-kilometre scale distances. The application of this approach has the potential to considerably reduce design uncertainty and ultimately reduce levelised costs of offshore wind power generation.

Deep Neural Networks for Detection and Location of Microseismic Events and Velocity Model Inversion from Microseismic Data Acquired by Distributed Acoustic Sensing Array

Fiber-optic cables have recently gained popularity for use as Distributed Acoustic Sensing (DAS) arrays for borehole microseismic monitoring due to their physical robustness as well as high spatial and temporal resolutions. As a result, the sensors record large amounts of data, making it very difficult to process in real-/semi-real-time using the conventional processing routines. We present a novel approach, based on deep learning, for handling the large amounts of DAS data in real-/semi-real-time. The proposed neural network was trained on synthetic microseismic data contaminated with real-ambient noise from field data and was validated using field DAS microseismic data obtained from a hydraulic fracturing operation. The results indicate that the trained network is capable of detecting and locating microseismic events from DAS data and simultaneously update the velocity model to a high degree of precision. The mean absolute errors in the event locations and the velocity model parameters are 2.04, 0.72, 2.76, 4.19 and 0.97 percent for distance (x), depth (z), P-wave velocity, S-wave velocity and density, respectively. In addition to automation and computational efficiency, deep learning reduces human expert data handling during processing, thus preserving data integrity leading to more accurate and reproducible results.

Seismic Applications of Downhole DAS

Distributed Acoustic Sensing (DAS) is gaining vast popularity in the industrial and academic sectors for a variety of studies. Its spatial and temporal resolution is ever helpful, but one of the primary benefits of DAS is the ability to install fibers in boreholes and record seismic signals in depth. With minimal operational disruption, a continuous sampling along the trajectory of the borehole is made possible. Such resolution is highly challenging to obtain with conventional downhole tools. This review article summarizes different seismic uses, passive and active, of downhole DAS. We emphasize current DAS limitations and potential ways to overcome them.