Fault-seal analysis in the Greater Bay du Nord area, Flemish Pass Basin, offshore Newfoundland
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
A 3D subsurface structural model was built in a zone of the Greater Bay du Nord area, Flemish Pass Basin, offshore Newfoundland and Labrador, to carry out a post-drilled, fault-seal analysis in a multi-rift, geological complex setting; this aimed to test fault-seal predictions, calibrate computed static fault-zone attributes and estimate hydrocarbon contact depths. Hydrocarbon exploration campaigns in the Greater Bay du Nord area have primarily targeted rotated fault blocks that often exhibit structural segmentation and compartmentalization. A comprehensive approach that combines empirical and deterministic methods for static fault-seal analysis has been implemented. This approach provides insights into open, base and tight fault-seal scenarios, aiding prospect evaluation in this region. Notably, shale gouge ratios (SGRs) in the range 16–25% serve as a crucial indicator of the transition between fault-rock sealing and non-sealing fault segments. Furthermore, it emphasizes the critical role of hydrodynamics when calibrating or evaluating fault-sealing properties. In areas like the Greater Bay du Nord region, characterized by complex geology, it is imperative to regularly update fault-seal models. These updates should align with the availability of new subsurface data, comprehensive analyses and an improved understanding of the petroleum system. Thematic collection: This article is part of the Fault and top seals 2022 collection available at: https://www.lyellcollection.org/topic/collections/fault-and-top-seals-2022
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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