Thermal Formation Damage and Relative Permeability of Oil Sands of the Lower Cretaceous Formations in Western Canada
Bibliographic record
Abstract
Abstract Canada ranks third in the world in terms of oil reserves which are primarily heavy oil and oil sands. In situ production of heavy oil and bitumen by thermal methods based on steam injection is a commercial technology. However, as the availability of better quality deposits is declining, the industry is moving towards development of lower quality oil sands. Lower quality oil sands are typically finer, have lower initial oil saturation and a more complex mineralogy. Thermal formation damage associated with steam injection is discussed in the paper in regards to oil sands located in the Lower Cretaceous formations in Western Canada. The focus of the paper is the McMurray, Clearwater and Grand Rapids oil deposits. Petrographic data (thin section analysis, X-ray diffraction and scanning electron miscroscopy) and physical rock properties are used to compare three oil sand formations. Results of laboratory experiments to obtain relative permeability data and evaluate thermal formation damage are discussed. Examples of the high temperature-high pressure water-oil relative permeability and steamflood data for three formations are presented. The paper shows that thermal formation damage is reservoir specific. A multidisciplinary approach is needed to obtain a good understanding of oil sand deposits, in particular lowerquality reservoirs. Laboratory testing to evaluate formation damage effects and obtain relative permeability data is essential for reservoir simulation and feasibility studies for a specific project.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".