ALBERT

Description: Methane hydrate is an ice-like substance that is stable at high-pressure and low temperature in continental margin sediments. Since the discovery of a large number of gas flares at the landward termination of the gas hydrate stability zone off Svalbard, there has been concern that warming bottom waters have started to dissociate large amounts of gas hydrate and that the resulting methane release may possibly accelerate global warming. Here, we can corroborate that hydrates play a role in the observed seepage of gas, but we present evidence that seepage off Svalbard has been ongoing for at least three thousand years and that seasonal fluctuations of 1-2°C in the bottom-water temperature cause periodic gas hydrate formation and dissociation, which focus seepage at the observed sites.

Description: Hyperspectral seafloor surveys using airborne or spaceborne sensors are generally limited to shallow coastal areas, due to the requirement for target illumination by sunlight. Deeper marine environments devoid of sunlight cannot be imaged by conventional hyperspectral imagers. Instead, a close-range, sunlight-independent hyperspectral survey approach is required. In this study, we present the first hyperspectral image data from the deep seafloor. The data were acquired in approximately 4200 m water depth using a new Underwater Hyperspectral Imager (UHI) mounted on a remotely operated vehicle (ROV). UHI data were recorded for 112 spectral bands between 378 nm and 805 nm, with a high spectral (4 nm) and spatial resolution (1 mm per image pixel). The study area was located in a manganese nodule field in the Peru Basin (SE Pacific), close to the DISCOL (DISturbance and reCOLonization) experimental area. To test whether underwater hyperspectral imaging can be used for detection and mapping of mineral deposits in potential deep-sea mining areas, we compared two supervised classification methods, the Support Vector Machine (SVM) and the Spectral Angle Mapper (SAM). The results show that SVM is superior to SAM and is able to accurately detect nodule surfaces. The UHI therefore represents a promising tool for high-resolution seafloor exploration and characterisation prior to resource exploitation.

Description: The seismic data were acquired north of the Knipovich Ridge on the western Svalbard margin during cruise MSM21/4. They were recorded using a Geometrics GeoEel streamer of either 120 channels (profiles p100-p208) or 88 channels (profiles p300-p805) with a group spacing of 1.56 m and a sampling rate of 2 kHz. A GI-Gun (2×1.7 l) with a main frequency of ~150 Hz was used as a source and operated at a shot interval of 6-8 s. Processing of profiles p100-p208 and p600-p805: Positions for each channel were calculated by backtracking along the profiles from the GI-Gun GPS positions. The shot gathers were analyzed for abnormal amplitudes below the seafloor reflection by comparing neighboring traces in different frequency bands within sliding time windows. To suppress surface-generated water noise, a tau-p filter was applied in the shot gather domain. Common mid-point (CMP) profiles were then generated through crooked-line binning with a CMP spacing of 1.5625 m. A zero-phase band-pass filter with corner frequencies of 60 Hz and 360 Hz was applied to the data. Based on regional velocity information from MCS data [Sarkar, 2012], an interpolated and extrapolated 3D interval velocity model was created below the digitized seafloor reflection of the high-resolution streamer data. This velocity model was used to apply a CMP stack and an amplitude-preserving Kirchhoff post-stack time migration. Processing of profiles p400-p500: Data were sampled at 0.5 ms and sorted into common midpoint (CMP) domain with a bin spacing of 5 m. Normal move out correction was carried out with a velocity of 1500 m s-1 and an Ormsby bandpass filter with corner frequencies at 40, 80, 600 and 1000 Hz was applied. The data were time migrated using the water velocity.