A Workflow for Optimization of Flow Control Devices in SAGD
Bibliographic record
Abstract
In McMurray Formation, steam assisted gravity drainage is used as the primary in-situ recovery technique to recover oil sands. Different geological reservoir settings and long horizontal wells impose limitations and operational challenges on the implementation of steam-assisted gravity drainage (SAGD). The dual-string tubing system is the conventional completion scheme in SAGD. In complex reservoirs where dual-string completion cannot improve the operation performance, operators have adopted flow control devices (FCDs) to improve project economics. FCDs secure more injection/production points along the horizontal sections of the SAGD well pairs, hence, they maximize ultimate bitumen recovery and minimize cumulative steam-oil ratio (cSOR). This paper will focus on the optimization of outflow control devices (OCDs) in SAGD reservoirs with horizontal wellbore undulations. We present the detailed optimization workflow and show the optimization results for various scenarios with well pair trajectory undulation. Comparing the results of the optimized OCDs case with a dual-string case of the same SAGD model shows improvements in steam distribution, steam chamber growth, bitumen production, and net present value (NPV).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".