An Overview of the Field Performance of Tubing Deployed Flow Control Devices in the Surmont SAGD Project
Bibliographic record
Abstract
Abstract Flow Control Devices (FCDs) are known to enhance efficiency of oil production, overall project economics and environmental performance that is currently of particular importance for Steam Assisted Gravity Drainage (SAGD) operators in Western Canada. FCDs have been utilized in SAGD wells over a decade, primarily, as liner deployed (LD) applications. Compared to LD FCDs, tubing deployed (TD) FCDs for SAGD producers are less common and require better understanding from the standpoint of completion design and operational strategy. A study has been conducted on TD FCD installations in producer wells in the Surmont SAGD project. The study was aimed to understand failure modes and causes for several failed SAGD producers retrofitted with TD FCDs. Due considerations were given to key factors such as geology, runtime, operational practices and the possibility of failure of the slotted liner. Caliper log, fiber optics and downhole imaging data were used in the study. FCD strings pulled from the ground have been also analyzed. All failures were found to be erosive wear with localized full wall loss of the TD FCD base pipe. No detectable erosion or other damage to FCDs are observed. As a general practice, a less aggressive operation strategy for wells with TD FCD compared to wells with LD FCDs was implemented after the study to avoid new failures. Proper screen sizing for TD FCD retrofits in slotted liner wells was identified as an important factor to provide effective sand control and may help reduce failures, but screen sizing was found not to have a direct effect on the failures investigated. The study shows that TD FCD retrofits have proven to be successful; however, special considerations are required when designing TD FCDs installations for SAGD producers, compared to LD FCDs, in order to reduce risk of erosive damage and failure.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".