New Results on the Structure of Iconic Rifted Continental Margins by Revising Legacy Seismic Datasets: The Newfoundland Margin
Abstract
Models of continental margins evolution are largely based on incomplete information, much of it built on research that is now >20 years old. Recent developments in parallel computing and novel geophysical approaches provide now the means to obtain a new look at the structure with radically superior resolution seismic models and a mathematically-robust analysis of the data uncertainty, that was formerly difficult, if not unfeasible, to achieve. Thus, we focused on the Newfoundland margin and applied bleeding-edge methodologies to a high-quality dataset acquired in 2000. The SCREECH data includes three primary transects with coincident multichannel seismic reflection data acquired on a 6-km streamer and wide-angle data recorded by short-period OBS and OBH spaced at ~10-20 km. This dataset was processed >15 years ago with now outdated methodologies. This re-processing in an HPC environment provided the high-resolution images that are needed to fulfill the characterization of this margin.
In particular, we performed joint inversion of multichannel and wide-angle seismic data, which drastically improved the resolution of the velocity model, which was subsequently used to perform a Pre-Stack Depth Migration of the multichannel data. The higher resolution of these images allows characterization of the different crustal domains of the margin in detail, as well as its tectonic structure. Altogether, these results provide the high-resolution images needed to understand the formation and evolution of the Newfoundland margin. Comparation of these results on the Newfoundland margin with the recent data on the West Iberian margin, acquired during the cruises FRAME (2018) and ATLANTIS (2022) (PI: C. Ranero, streamer data and coincident closely-spaced OBS data), provides a unique opportunity to improve our knowledge on the evolution of the North Atlantic opening.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFM.T26B..05G