Quantitative interpretation of the McKay oil sands thermal area: Canadian case study
Bibliographic record
Abstract
Southern Pacific Resource Corporation (STP) acquired 211 km of 2D seismic data in September 2007 and an additional 5.1 km2 of 3D in December 2010. The 2D survey was used as an exploration tool, which ultimately lead to the McKay Thermal Project in northeastern Alberta. Conventional seismic interpretation has been valuable in defining the structure and regional extent of the reservoir. However, the conventional seismic character lacks the detail or consistency to delineate subtle facies variations present in the reservoir. Risk reduction through increased understanding of the reservoir at this stage of an oil sands project has the potential for significant benefits as the project moves on to production. Seismic data have already proven beneficial in the evaluation phase of this project; the intent with this case study was to investigate the potential to derive more detailed information from the seismic about the reservoir character and fluid content using quantitative interpretation (QI) techniques.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".