Complex fault growth controls 3-D rift geometry: Insights from deep learning of seismic reflection data from the entire northern North Sea rift

Understanding how normal faults grow is critical to an accurate assessment of seismic hazards, for successful exploration of natural (including low-carbon) resources and for safe subsurface carbon storage. Our current knowledge of fault growth is, in large parts, derived from seismic reflection data of continental rifts and margins. These seismic datasets do however suffer from limited data coverage and resolution. In addition, detailed fault mapping in increasingly large seismic reflection data requires a large amount of expertise and time from interpreters. Here we map faults across the entire northern North Sea rift using a combination of supervised deep learning and broadband 3-D seismic reflection data. This approach requires us to interpret 90%) are closely spaced (< 5 km) and relatively short (