Application of 3D marine CSEM finite-element forward modeling to hydrocarbon exploration in the Flemish Pass Basin offshore Newfoundland, Canada
Bibliographic record
Abstract
Recent seismic data acquired in the Flemish Pass Basin offshore Newfoundland shows AVO anomalies in three Tithonian age sands up-dip from where a well was drilled, Mizzen L-11. As an alternative to fluid substitution, this study considers marine CSEM forward modeling to assess the reservoir potential and de-risk the L-11 prospect. The 3D models were built by incrementally adding surfaces to gradually increase complexity resulting in four distinct models. The constructed models were able to reflect the necessary scale and complexity of the Flemish Pass Basin. In summary, the marine CSEM results generated from these models were of good quality and matched well with the measured data. Sensitivity to the Mizzen L-11 reservoir was found, but it may be below the detectability threshold. However, the L-11 reservoir is quite small and if the reservoir had been of sufficient size (equivalent to the size of its neighbor at O-16) a measurable sensitivity would be present. Presentation Date: Wednesday, October 19, 2016 Start Time: 10:45:00 AM Location: 174 Presentation Type: ORAL
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".