Well log analysis at the White Rose oilfield, offshore Newfoundland
Bibliographic record
Abstract
The petrophysical analysis in this paper is based on dipole sonic (Vp and Vs), density, gamma-ray, and porosity (density porosity and neutron porosity) logs from wells in the White Rose oilfield, offshore Newfoundland. In general, Vp and Vs increase with depth, Vp/Vs decreases with depth, velocity increases as total porosity decreases, Vp/Vs decreases slightly when total porosity decreases, and Vs shows a high correlation with porosity. We also applied empirical Castagna’s (1985), Faust’s (1951), Gardner et al.’s (1974) and Pickett’s (1963) relationships. We find that Faust is the better predictor for Vp, Castagna is a better predictor for Vs, Castagna’s limestone relationship works better than Pickett’s limestone relationship, and the Gardner prediction of ρ should be used with caution. Empirical relationships apply with a variable levels of accuracy. Better fits can be achieved by dividing the lithologies into formations (Jaramillo and Stewart, 2003).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".