Seal bypass at the Giant Gjallar Vent (Norwegian Sea): Indications for a new phase of fluid venting at a 56-Ma-old fluid migration system

Abstract

The Giant Gjallar Vent (GGV), located in the Vøring Basin off mid-Norway, is one of the largest (~5 × 3 km) vent systems in the North Atlantic. The vent represents a reactivated former hydrothermal system that formed at about 56 Ma. It is fed by two pipes of 440 m and 480 m diameter that extend from the Lower Eocene section up to the Base Pleistocene Unconformity (BPU). Previous studies based on 3D seismic data differ in their interpretations of the present activity of the GGV, describing the system as buried and as reactivated in the Upper Pliocene. We present a new interpretation of the GGV's reactivation, using high-resolution 2D seismic and Parasound data. Despite the absence of A C C E P T E D M A N U S C R I P T ACCEPTED MANUSCRIPT2 geochemical and hydroacoustic indications for fluid escape into the water column, the GGV appears to be active because of various seismic anomalies which we interpret to indicate the presence of free gas in the subsurface. The anomalies are confined to the Kai Formation beneath the BPU and the overlying Naust Formation, which are interpreted to act as a seal to upward fluid migration. The seal is breached by focused fluid migration at one location where an up to 100 m wide chimney-like anomaly extends from the BPU up to the seafloor. We propose that further overpressure build-up in response to sediment loading and continued gas ascent beneath the BPU will eventually lead to large-scale seal bypass, starting a new phase of venting at the GGV.

Prediction of seismic P-wave velocity using machine learning

“…A 10-fold cross validation (CV), an approach frequently used in model validation (e.g. Li et al, 2011;Gasch et al, 2015;Ließ et al, 2016;Meyer et al, 2016bMeyer et al, , 2018, was applied to validate the RF model. CV involved partitioning the dataset into 10 equally sized folds.…”

“…Seismic velocities can also be obtained indirectly from seismic data. Approaches include derivation of 1-D velocity profiles via refraction seismology using ocean bottom seismometers (OBSs) (Bünz et al, 2005;Mienert et al, 2005;Westbrook et al, 2008;Plaza-Faverola et al, 2010a, b, 2014, and velocity analysis of large-offset reflection seismic data (Crutchley et al, 2010(Crutchley et al, , 2014Plaza-Faverola et al, 2012). However, suitable seismic datasets are only available in certain areas, and OBS-derived velocity profiles are of relatively low spatial and vertical resolution.…”

“…In the absence of measurements and refraction seismic data, constant velocities are often used for time-depth conversions (e.g. Brune et al, 2010) or processing of reflection seismic data (Crutchley et al, 2010(Crutchley et al, , 2011(Crutchley et al, , 2013Netzeband et al, 2010;Krabbenhoeft et al, 2013;Dumke et al, 2014), even though a constant velocity-depth profile is generally unrealistic and will thus lead to inaccurate results.…”

“…Lary et al, 2016). In geosciences and remote sensing, machine learning methods have been used to predict soil properties (Gasch et al, 2015;Ließ et al, 2016;Meyer et al, 2018), air temperatures (Meyer et al, 2016a(Meyer et al, , 2018, biomass (Meyer et al, 2017), and the elasticity modulus of granitic rocks (Karakus, 2011). Applications also extended into marine settings, involving the prediction of sediment mud content off southwest Australia (Li et al, 2011), as well as parameters such as seafloor porosity (Martin et al, 2015;Wood et al, 2018), seafloor biomass (Wei et al, 2010), and seafloor total organic carbon (Wood et al, 2018;Lee et al, 2019) on a global scale.…”

Prediction of seismic p-wave velocity using machine learning

“…25 In the absence of measurements and refraction seismic data, constant velocities are often used for time-depth conversions (e.g. Brune et al, 2010) or processing of reflection seismic data (Crutchley et al, 2010(Crutchley et al, , 2011Netzeband et al, 2010;Krabbenhoeft et al, 2013;Dumke et al, 2014), even though a constant velocity-depth profile is generally unrealistic and will thus lead to inaccurate results. Solid Earth Discuss., https://doi.org /10.5194/se-2019-58 Manuscript under review for journal Solid Earth Discussion started: 4 April 2019 c Author(s) 2019.…”