Bibliographic record
Abstract
Abstract The SAGD process has already been implemented for commercial production in Alberta Oil Sands areas in Western Canada since early 2000. SAGD performance is very sensitive to reservoir heterogeneities such as shale barriers, bottom and/or top water zones, and a gas cap. In the SAGD process, low permeability zones such as shale layers may act as a flow barrier depending on their size, vertical and horizontal locations, and continuity throughout the reservoir thus making it very important to understand and characterize the effect of shale layers. In this study, the impact of various sizes and locations of shale barriers have been investigated through two-dimensional hypothetical simulation models. The various simulation models have been designed to investigate the shale size and vertical location in both BIP (shale between the injector and producer) and AP (shale above the producer) cases. Two different types of models were designed to look at the effect of flow path existence between the injector and producer: type-A is designated as having a no flow path directly above the producer and type-B has a flow path directly above the producer. The simulation results show that type-A has a greater impact than type-B on SAGD performance especially for the BIP case. Small shale sizes of 3 and 5 m have a slight impact on performance; however, cases with 10 m shale have a greater impact due to the disruption of gravity drainge to the producer. Type-A BIP may require a longer pre-heating period for successful SAGD operation. Generally, shale barriers of 5 to 25 m are not critical for an AP case regardless of vertical location of shale barriers; however shale barriers greater than 50 m may act as a barrier and reduce the effective pay thickness of the reservoir depending upon the its vertical location.
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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 | 0.000 | 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".