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Ocean Science An interactive open-access journal of the European Geosciences Union
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Volume 8, issue 2 | Copyright
Ocean Sci., 8, 175-181, 2012
https://doi.org/10.5194/os-8-175-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.

Technical note 14 Mar 2012

Technical note | 14 Mar 2012

Technical Note: Detection of gas bubble leakage via correlation of water column multibeam images

J. Schneider von Deimling1,2 and C. Papenberg2 J. Schneider von Deimling and C. Papenberg
  • 1Leibniz Institute for Baltic Sea Research, Rostock, Germany
  • 2Leibniz Institute of Marine Sciences, Helmholtz Centre for Ocean Research (GEOMAR), Kiel, Germany

Abstract. Hydroacoustic detection of natural gas release from the seafloor has been conducted in the past by using singlebeam echosounders. In contrast, modern multibeam swath mapping systems allow much wider coverage, higher resolution, and offer 3-D spatial correlation. Up to the present, the extremely high data rate hampers water column backscatter investigations and more sophisticated visualization and processing techniques are needed. Here, we present water column backscatter data acquired with a 50 kHz prototype multibeam system over a period of 75 seconds. Display types are of swath-images as well as of a "re-sorted" singlebeam presentation. Thus, individual and/or groups of gas bubbles rising from the 24 m deep seafloor clearly emerge in the acoustic images, making it possible to estimate rise velocities. A sophisticated processing scheme is introduced to identify those rising gas bubbles in the hydroacoustic data. We apply a cross-correlation technique adapted from particle imaging velocimetry (PIV) to the acoustic backscatter images. Temporal and spatial drift patterns of the bubbles are assessed and are shown to match very well to measured and theoretical rise patterns. The application of this processing to our field data gives clear results with respect to unambiguous bubble detection and remote bubble rise velocimetry. The method can identify and exclude the main source of misinterpretations, i.e. fish-mediated echoes. Although image-based cross-correlation techniques are well known in the field of fluid mechanics for high resolution and non-inversive current flow field analysis, we present the first application of this technique as an acoustic bubble detector.

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