An Overview of Surmont SAGD ESP Gas Handling Project to Mitigate Production Effects of NCG Co-Injection
Bibliographic record
Abstract
Abstract NCG (Non-Condensable Gas) co-injection with steam has been in operation at Surmont SAGD field since 2017. After a significant number of operational attempts to mitigate ESP no flow events (deadheading) suspected to be instigated by increased production of gas (typical SAGD GOR 5-10 m3/m3) a strategy was developed to focus on completion adjustments to the ESP on candidate SAGD producers. These changes were completed in late 2019 to help reduce the loss of production, which could impact viability of NCG co-injection at Surmont. Three separate completion adjustments were made: an inverted shroud installation, a larger OD pump with a gas separator, and lowering of an ESP to the lowest possible TVD. A comparison of the production and operational performance before and after each completion adjustment was completed. In-depth design reviews between CPC and the equipment vendor were done to ensure maximum chance of positive benefit. The inverted shroud installation was expected to improve gas separation efficiency, leading to a reduction in the frequency of No Flow Events (NFEs), which were impacting production rates. The shrouded ESP performance on the first candidate well showed no NFEs with a significant increase in production rates compared to the baseline before the completion adjustment. The larger OD pump with gas separator install was also expected to reduce or completely prevent NFEs. the results were also positive, with an increase in production and no further NFEs recorded. Lowering of a third ESP to a point as close as possible to the liner hanger did not achieve any long-term change in production performance. With the success of the inverted shroud, a second installation was completed on the third well where the ESP was being lowered. A production increase and prevention of NFEs were documented like the first shroud installation, confirming the benefit of the shrouded ESP design. The completion changes confirmed that suitable adjustments to mitigate the effects of NCG injection are possible, with further development on design required to optimize for production capacity and long-term performance. With the results seen so far, further installations will be completed in the future on appropriate candidates to continue to mitigate the effect on ESPs of produced NCG volumes.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".