Numerical Simulation of SAGD with Vertical Slimholes
Bibliographic record
Abstract
Abstract Steam assisted gravity drainage is the primary in-situ recovery method for bitumen from the large Athabasca deposit in Alberta, Canada. SAGD field operations encounter a significant decrease in production performance when low permeability shale barriers are present in the formation. These layers can reduce SAGD performance and impede the growth of the steam chamber. They also significantly limit the percentage of the deposit where bitumen can be economically recovered with SAGD. The concept of drilling vertical slimholes to create flow paths through barriers was conceived and investigated at Alberta Innovates - Technology Futures (formerly the Alberta Research Council). Use of slimholes has the potential to significantly increase the amount of recoverable bitumen (reserves) and the rate at which it is produced during SAGD. For shallow reservoirs, the slimholes could be drilled from the surface at relatively low cost. 2-D and 3-D field scale numerical simulations were performed using reservoir properties and operating conditions that were based on published information for the MacKay River SAGD operation in the Athabasca deposit. The reservoir depth was 135 m, the initial pressure 500 kPaa, the initial temperature 7.5 °C, and the initial oil saturation 0.8. The simulations explored the impact of vertical slimholes, which were 7 m laterally offset from the horizontal well pair (Figure 1), on reservoirs with and without shale layers or shale lenses. The effect on SAGD performance of slimhole cross-section (25 cm × 25 cm or 50 cm × 50 cm) and distance between slimholes (12 m or 24 m in the direction parallel to the well pair was investigated). The effect of reservoir and slimhole permeability and the impact of horizontal slimholes from the injector or producer were also explored. The slimholes were represented by high permeability vertical channels using refined grids. Counter-current flow of gas and liquid through the slimholes was represented by adjusting the relative permeability in the slimholes. For a reservoir, with a continuous shale layer, SAGD performance was improved by vertical slimholes due to the recovery of previously inaccessible oil from above the shale layer where a secondary steam chamber was formed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".