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QPS Client Spotlight: Ghent University

Evaluating seep activity in Space and Time

About Renard Centre of Marine Geology (RCMG), Ghent University

The RCMG has been a QINSy and Fledermaus client for over ten years (first purchasing in 2004). In the early days of using Fledermaus the staff and students were "Fledermaus Standard" users, what was then the equivalent of our current FM Viz4D visualization bundle. Since then they have upgraded to FM Pro, giving them the ability to create PFMs and do bathymetric editing, and have added FMMidwater for water column data processing. The RCMG has ongoing research in geophysics, continental margin geology, limnogeology, methane hydrates, cold-seeps, and mud volcanoes, cold-water corals and carbonate mud mounds, marine habitat mapping, and marine environmental and geoarcheological research. To facilitate their research, they have a well-developed research infrastructure that includes high and very-high resolution refection seismic equipment, a Klein 3000 sidescan sonar, a Seabeam 1050 multibeam sonar, lake coring equipment, and a core analysis facility.

International collaboration to study methane gas emissions in the Arctic

The Arctic region comprises large and varied reservoirs of methane (from both terrestrial and marine sources). Gas hydrates within continental slope sediments or associated with permafrost underneath the Arctic shelves represent one of them. The stability of these hydrates is determined by environmental conditions (pressure, temperature) and changes in these conditions may cause the hydrates to dissociate and free gas to be released at the sea floor. A series of international surveys were conducted during 2009, 2010, 2012 and 2013 in order to detect and map the seep sites and monitor the activity of this phenomenon. The research has also been part of COST (European Cooperation in Science and Technology) Action PERGAMON (PERmafrost and GAs hydrate related methane release in the Arctic and impact on climate change: European cooperation for long-term MONitoring; http://www.cost-pergamon.eu). 

Contributors to this project were:  Mario Veloso (1, 2), Jens Greinert (1,2,3,4), Jurgen Mienert (4) and Marc De Batist (1). The institutions involved are: 

(1)   Renard Centre of Marine Geology (RCMG), Ghent University, Ghent, Belgium.

(2)   GEOMAR Helmholtz Centre for Ocean Research, Kiel, Germany.

(3)   Royal Netherlands Institute for Sea Research (NIOZ), Den Burg, Netherlands.

(4)  Centre for Arctic Gas Hydrate, Environment and Climate (CAGE), Department of Geology, The Arctic University of Norway (UiT), Tromso, Norway.

Figure 1. An overview map of the study area; the color bar shows water depth is in meters. Selected contours are additional indications of water depth, and white points mark locations of the detected acoustic flares.

Figure 2. Close-up view of survey area. The colors in the image on the left show indicate the volume scattering strength (Sv) in dB

Methane gas emissions at underwater seep sites off the coast of Svalbard (W-Spitsbergen, ~78° N) have been associated with the decomposition of hydrates caused by the slow warming of the northward Atlantic waters (Westbrook et al., 2009).

During the surveys, hydroacoustic data was acquired with multibeam and single-beam sonar systems. Data recorded with the scientific split-beam echosounder Simrad EK60 has been analysed and processed to obtain physical parameters of the seep sites. A specialized graphical user interface created in Matlab (FlareHunterhttp://www.geomar.de/en/research/fb2/fb2-mg/deepsea-monitoring/software/flarehunter-and-fluxmodule/) was created and using the data of the spatial distribution inside the beam (electrical angles acquired with the split-beam method) 3D information was obtained of the backscattering pattern produced by the rising gas bubbles. Using this information, it was possible to find tendencies and the average locations of each seep site (which can be formed by several bubble streams). Locations of seep sites from different echograms were compared in order to avoid overestimation of the number of acoustic flares. Also, flare positions were compared to know the spatial variability of the seep site area between the different years. In addition, information about bubble rising speed was extracted from the echograms. This information was compared with visual observations obtained with a video camera in order to obtain an estimation of the bubble size distribution (BSD) of the gas bubbles released at the different seep sites. Information of the target strength (TS) of each seep site was obtained as well.

Integrating all the mentioned information creates a quantitative map of the bubble release in the study area. This will help to improve understanding of the dynamics of the processes involved as a function of time and space, and consequently assist in assessing the potential of the released methane to reach the atmosphere and future impacts on climate change.

Figure 3. Flare spines over four survey seasons, displayed in Fledermaus.

How Fledermaus was used on this project

The Fledermaus suite was used for analysis and post-processing of the data captured with the Kongsberg EM300 multibeam echosounder. Multibeam data processing was done with DMagic and Fledermaus (Fig.5 and Fig.6); DMagic was used to create an editable file PFM file, which was then loaded into Fledermaus for visualization and editing.

Figure 4. Multibeam data displayed in Fledermaus.

Once in Fledermaus, data was extracted and edited using the 3D Editor. The editing of the multibeam data included rejecting points outside the spatial tendency of the surface. Once the PFM file was completely edited, a DTM SD was created showing the fully cleaned surface. Later, the DTM SD file can be loaded in Fledermaus or DMagic and the surface data can be exported in different formats (XYZ, GMT GRD, ArcGrid, Floating Point GeoTIFF, or Google Earth KMZ), making it easy to share the cleaned surface data with colleagues who are using other tools. Additionally, Fledermaus was used to integrate data extracted from the echosounder (e.g. sonar curtains, xyz positions of bubble release) with the edited bathymetry (Fig. 3, Fig 7b, and Fig. 8). Both multibeam and single beam data have been displayed in Fledermaus in order to analyze whether there was any relationship between features on the seabed and the bubble release. No evidence was found.

Figure 5. DMagic user interface used to create the editable PFM file for bathymetry corrections


Figure 6. 3D editor interface used to delete ("reject") points during bathymetry correction.


Figure 7. Screenshot from Fledermaus showing a) Edited bathymetry of the study area and b) Integrated data for visualisation. Image 7b shows the corrected bathymetry (grey), the sonar curtains created in FMMidwater, and the GPS track of one of the campaigns.


Figure 8. Integrated data for visualisation. The image shows the edited bathymetry of the study area with the calculated flare spines and gas release spot positions.

The visualisation of the data recorded with the singlebeam system (EK60 split-beam echosounder) was done using the FMMidwater module. Files containing gas plumes (also known as acoustic flares) were uploaded into FMMidwater to register GPS positions of the vessel when a flare was detected in the echogram. Heights of acoustic flares (distance between the seafloor and the top of the flare) were measured with FMMidwater using the Geo Pick tool. Additionally, bubble rising speed measurements were carried out when single bubbles were identified in the echograms. Finally, sonar curtains in SD format were exported from FMMidwater for direct integration with the bathymetry data in Fledermaus, completing the visualization.

Figure 9. Screenshot of an echogram from singlebeam data visualised in the FMMidwater module. To calculate the bubble rising speed, single bubbles were identified and average rising speed was calculated through dividing the ascended distance by the elapsed time.  These values have been used to obtain estimations of gas fluxes using a hydroacoustic inverse method (Muyakshin and Sauter, 2010). 

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