Partial-SAGD Applications in the Jackfish SAGD Project
Bibliographic record
Abstract
Summary With steam-assisted-gravity-drainage (SAGD) operations, there will be times that the producer downhole temperature falls below the desired level. This situation may occur when a shut-in is required because of facility or well operational issues. Cooling bitumen and steam condensate, which continue to drain and raise the liquid level over the producer, cause difficulties with the restart. The producer could also cool if the well pair is converted prematurely from circulation to full SAGD mode. A variety of artificial-lift technologies have been applied in field applications. However, with its dual-tubing-completion design and gas lift system, Devon has successfully used partial SAGD methods to optimize restart strategies and effectively deal with times when the producer unexpectedly cools. This paper describes three SAGD operating modes used by Devon at Jackfish: full SAGD, semi-SAGD, and partial SAGD. During partial SAGD, the fluid return from the injector stops while steam injection continues down either the long tubing (LT), short tubing (ST), or the annulus. The producer continues to be circulated with the appropriate steam-injection rate into the LT and fluid returns up the ST. Numerical-simulation results associated with partial SAGD are presented. Partial-SAGD applications at the Jackfish SAGD project are discussed.
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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 | 0.001 |
| 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 | 0.001 |
| 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".