The Influence of Grain Morphology on Reservoir Quality of Some Athabasca Oil Sands Samples
Bibliographic record
Abstract
This study focused on the determination of detailed grain morphology using SEM technology on some Athabasca oil sands samples obtained from the Upper McMurray Formation in the Manville Group which occurs in the Western Canada Sedimentary Basin. The research was carried out using scientific techniques to understand grain morphology—being a major effect in discerning reservoir quality—a factor which is essential for in-situ bitumen recovery. After studying various grain size and shape parameters, results showed that Sample B is poorly sorted medium sand of relatively low porosity but high permeability. Sample C on the other hand is moderately sorted fine sand of relatively high porosity but low permeability. It was also found out that although both oil sand samples contain heavy oil which is essentially recoverable in-situ; Sample B proved to be more promising due to its higher permeability values. At the end of the study, it was recommended that further research be carried out on the oil sands samples by use of core analysis techniques; computer-based simulation for heavy oil recovery; and a general study of structural effects on oil sands such as weathering and fracturing, all of which are important in better-quality in-situ bitumen recovery.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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 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".