Optimization of SAGD Wellbore Completions: Short Production Tubing String Sensitivities
Bibliographic record
Abstract
Abstract A simulation study was carried out to examine the effects of changing the landing position of the short production tubing string relative to the heel of a SAGD production well. A homogeneous discretized wellbore model with the riser section was used in this study. Generally, a reservoir is modeled independent of the wellbore. However, this study models the reservoir and wellbore simultaneously to understand the interactions between them. This paper outlines two independent case studies, which are outlined below: The first study involved shortening the short production tubing string relative to the heel of the well. It was found that as the short tubing string was pulled back from the heel of the well the bitumen production rate decreased, and the amount of steam produced through the short production tubing string increased.The second case study outlines the impact of extending the short production tubing string past the heel of the well on bitumen production and SOR. From this case study, it was found that as the short production tubing string was pushed past the heel of the well, the bitumen production rate stayed the same, but the steam injection rate decreased which consequently decreased the SOR. It was also observed that a lower pressure differential between the injector and producer well was established when the short production tubing string was extended. The results for this study will assist SAGD producers to re-evaluate the position of the short production tubing string, and find the most economical position for this string. This paper creates the foundation for further simulation efforts to incorporate a discretized model with the build section coupled to the reservoir. This will allow production engineers to optimize bitumen production by simultaneously simulating the reservoir and wellbore strings together.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".