ALBERT

Beschreibung: In 1964, exploration drilling in the German Sector of the North Sea hit a gas pocket at ∼2900 m depth below the seafloor and triggered a blowout, which formed a 550 m-wide and up to 38 m deep seafloor crater now known as Figge Maar. Although seafloor craters formed by fluid flow are very common structures, little is known about their formation dynamics. Here, we present 2D reflection seismic, sediment echosounder, and multibeam echosounder data from three geoscientific surveys of the Figge Maar blowout crater, which are used to reconstruct its formation. Reflection seismic data support a scenario in which overpressured gas ascended first through the lower part of the borehole and then migrated along steeply inclined strata and faults towards the seafloor. The focused discharge of gas at the seafloor removed up to 4.8 Mt of sediments in the following weeks of vigorous venting. Eyewitness accounts document that the initial phase of crater formation was characterized by the eruptive expulsion of fluids and sediments cutting deep into the substrate. This was followed by a prolonged phase of sediment fluidization and redistribution widening the crater. After fluid discharge ceased, the Figge Maar acted as a sediment trap reducing the crater depth to ∼12 m relative to the surrounding seafloor in 2018, which corresponds to an average sedimentation rate of ∼22,000 m 3 /yr between 1995 and 2018. Hydroacoustic and geochemical data indicate that the Figge Maar nowadays emits primarily biogenic methane, predominantly during low tide. The formation of Figge Maar illustrates hazards related to the formation of secondary fluid pathways, which can bypass safety measures at the wellhead and are thus difficult to control.

Beschreibung: High-resolution 3D seismic refraction data during research cruise MSM63 in April/May 2017 onboard RV Maria S. Merian. 15 ocean bottom seismometers sampled seismic shots around the Scanner Pockmark, central North Sea. Seismic data are in standard segy-format.

Beschreibung: Source data of the North Sea well inventory: United Kingdom (UK)- Oil and Gas Authority (Dec. 2018) - https://data-ogauthority.opendata.arcgis.com/datasets/oga-wells-ed50 Contains information provided by the OGA. Wells are extracted for the area of the PGS data set PGS Mega Survey Plus. We measured the distance between all wells of the test group (n = 43) and all those who are within the seismic data set (n = 1,792; presented here) and their closest bright spot with polarity reversal. Furthermore, we calculated the mean RMS amplitudes and RMS amplitude standard deviation for a buffer radius of 300 m around the well paths for all wells inside the seismic data set and the visited wells as 300 m is the distance below which all of the visited wells of the test group showed gas release in form of flares from the seafloor. We test, if the propensity of a well to leak can be identified by using a logistic regression, which includes regressors such as well activity data and/or derived parameters such as mean RMS amplitude and mean RMS amplitude standard deviation, the distance towards the most proximal bright spot with polarity reversal and age (spud date). In order to identify the most suitable regressor combination best subset selection is employed. The main selection criterion chosen was the prediction accuracy from randomly and repeatedly splitting the visited wells into a training and a test set and then using the fitted logistic regression to predict the test data. The most suitable subset turns out to only employ the distance to polarity reversal, producing a prediction accuracy of 89% and the following logistic regression results: In order to obtain confidence intervals using the normal distribution the distance to bright spot with polarity reversal has to be normally distributed, which it is not. Yet it can be transformed to normality by adding 100 meters to the original distance and then taking the natural logarithm: Logistic regression fit for leakage of all visited wells using distance to bright spot with polarity reversal in meters as a regressor. Please find further information on the applied statistical analyses in the supplementary material. EstimateStd. Errorz valuePr(〉|z|)Significance Intercept4,853.9461,735.1282.7970.005150.01 Distance−0.0073610.002700−2.7260.006400.01 The transformed logistic regression model is then used to predict the probabilities of leakage for the wells within our seismic data set in the Central North Sea (here presented data). In order to obtain confidence bands this logistic regression is performed subtracting and adding two standard deviations from the calculated probability. The point estimate predicts leakage from 926 of the 1,792 wells, where the 95% confidence interval ranges from 719 to 1,058.

Beschreibung: Multibeam bathymetry raw data were recorded in the Mediterranean Sea during cruise SO277 (GPF 19-2_012) that took place between 2020-08-14 and 2020-10-03 (Emden-Emden). The data were collected using a vessel-mounted Kongsberg EM710. Sound velocity profiles (SVP) were applied on the data for calibration. Please see environmental data (zip file) and the cruise report for details. SO277 served two scientific projects. The objectives of the first project, SMART, were to develop multi-disciplinary methodologies to detect, quantify, and model offshore groundwater reservoirs in regions dominated by carbonate geology such as the Mediterranean Sea.

Beschreibung: Ocean Bottom and deep-towed controlled source electric field data during cruise MSM63 with electromagnetic source DASI (University of Southampton), electric field receivers Vulcan (UoS, Scripps), and Ocean bottom receivers (Ocean Bottom Instrument Facility, UK).

Beschreibung: High-resolution multibeam bathymetry data were collected during the 3D seismic survey (https://doi.pangaea.de/10.1594/PANGAEA.943506, https://doi.pangaea.de/10.1594/PANGAEA.943523). In 2006 onboard RRS Charles Darwin the EM-120 (13 kHz, 191 beams) was used. The data was processed to a 5x5 m grid.The data is fully processed and no additional data exist. The data is projected to UTM WGS 1984 31N.

Beschreibung: Underway temperature and salinity data was collected along the cruise track with two autonomous measurement systems, called self-cleaning monitoring boxes (SMBs). Usually, the SMBs are changed after 12 hours. While temperature is taken at the water inlet in about 3 m depth, salinity is estimated within the SMB from conductivity and interior temperature. No calibration was performed, neither for temperature nor for salinity. For details to all processing steps see Data Processing Report.

Beschreibung: Multibeam bathymetry raw data was recorded in the Pacific during cruise SO241 that took place between 2015-06-23 and 2015-07-24. The data was collected using the ship's own Kongsberg EM 120. This data is part of the DAM (German Marine Research Alliance) project Underway Research Data. Sound velocity profiles (SVP) were applied on the data for calibration. SVP data are part of this dataset publication. Please see the cruise report for details.

Beschreibung: This 2D multi-channel seismic data set was acquired during SONNE cruise SO241 offshore Mexico in the Guaymas Basin in June 2015. MCS data were collected using a Geometrics GeoEel streamer of variable active lengths, such as 150, 162, 175, and 187 m with 96, 104, 112, and 120 channels, respectively. The hydrophone group spacing was 1.56 m. The seismic source signal was generated by two generator-injector (GI) air guns, each with a volume of 210 cubic inches or 3.44 l (1.72 l generator and 1.72 l injector). The air guns were operated in harmonic mode at a tow depth of 2 m. The shot interval was 7 s, resulting in a mean shot point distance of 12 m. The recording time was 4 s, and the sampling rate was 1 ms. Navigation is based on ship GPS and lay backs. Locations are given in UTM zone 12N. Seismic data processing was funded by VBPR AS and carried out with RadExPro. It included common mid-point (CMP) binning with a CMP bin spacing of 3.125 m; band pass filtering using an Ormsby filter with corner frequencies of 20, 45, 250, and 400 Hz; normal move-out correction (NMO); and true amplitude recovery. The NMO-corrected gathers were stacked, and subsequently, a post-stack Stolt migration with 1500 m/s velocity was carried out. Detailed information on the data acquisition can be found in the SO241 cruise report (https://doi.org/10.3289/CR_S241).

Beschreibung: The 3D seismic cube is in SEG-Y format with SP in byte 5, inline number in byte 25 and xline number in byte 17. Processing includes repositioning, time migration and depth conversion using a smoothed velocity field based on Berndt et al., 2019. Acquisition parameters are discussed in the SO227 cruise report (Berndt et al., 2013).