Integrating streamer and ocean-bottom seismic data for sub-basalt imaging on the Atlantic Margin
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Stacked basalt flows cover much of the NW European continental margin, including potentially prospective sediments of the Faroes shelf. Such flows attenuate seismic energy, hindering sub-basalt structural imaging which is critical for both exploration and tectonic studies. Low-frequency, long-offset reflection surveys have yielded improved images below top basalt, while coincident ocean-bottom seismometer (OBS) data have mapped low velocity zones (LVZ) from tomographic inversion. Image correlation in a common depth domain is challenged by low spatial resolution of the tomographic image, the absence of turning rays in a LVZ and the lack of wide-angle arrivals in the reflection data. We integrate densely sampled reflection data with deep velocities from OBS data to give a common velocity model in a new, iterated, pre-stack depth-migration workflow using complementary constraints from the two datasets. The matched velocity model and depth image enable interpretation of (i) a uniform flood basalt sequence, 2–4 km thick beneath the Fugloy Ridge, with velocities correlating with those in the Lopra 1/1A borehole and (ii) a sub-basalt LVZ with chaotic reflections corresponding to sill-intruded, probably syn-rift sediments. Such a workflow could be extended to targets beneath high velocity salt or basalt and could provide constraints for 3D datasets. Supplementary material: Overlays of modelled arrival times on all the OBS gathers, similar to Figure 4, can be found at http://www.geolsoc.org.uk/SUP18433
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it