Semiautomated analysis of faults with meter-scale displacements and networks of planar features using high-resolution 3D seismic data to investigate gas leakage at the Vestnesa Ridge, Eastern Fram Strait
Year: 2024
Type: article
Abstract: We develop a semiautomated method for extracting faults and other planar features from two high-resolution (HR) seismic volumes in the eastern Fram Strait. We assess seismic data quality and resolution prior to structural interpretation to determine the appropriate processing workflow. This workflow, designed for HR data sets, identifies meter-scale (>3–4 m) faults and other planar features, picked up by subtle changes in the curvature and discontinuities of seismic reflections, to investigate their relationship with fluid migration in the shallow subsurface. Although evidence exists for Holocene (approximately <8 ka) fault-associated gas seepage, structures in both volumes are presently sealing. We assess structures based on those that have measurable throw (faults) and those that do not (planar features). Structures lacking measurable throw are significant because they appear to represent fluid flow pathways. This technique enhances the analysis of the geometries of the mapped structures, facilitating the interpretation of meter-scale fault throws and the orientations of planar features. We provide insights into the evolution of structures previously linked to episodes of fluid migration and gas leakage at the Vestnesa Ridge. We infer zones of dilation (i.e., opening) at locations where faults or networks of planar features interact and investigate how these structures influence localized uplift and shallowing of the interface between free gas and gas hydrate (i.e., the bottom-simulating reflection).
Source: Interpretation
Authors: Frances Cooke, Andreia Plaza-Faverola, Stefan Bünz, Paul de Groot, David C. P. Peacock
Institutions: UiT The Arctic University of Norway, University of Göttingen
Language: English
Subfield: Geology
Field: Earth and Planetary Sciences
Domain: Physical Sciences
Open Access status: green
Awards: G366195019, G5070530488
OpenAlex ID: W4404312988
