Successful Application of Hot-Water Circulation in the Pelican Lake Field: Results and Analyses of the E29 Hot-Water-Injection Pilot
Bibliographic record
Abstract
Summary The Pelican Lake field in northern Alberta (Canada) is home to the first successful commercial application of polymer flooding in higher-viscosity oils (i.e., greater than 1,000 cp), which has opened up new opportunities for the development of heavy-oil resources. The field produces from the Wabiskaw “A” reservoir, which has thin pay (2 to 6 m) and exhibits a significant viscosity gradient across the field, with oil viscosities as low as 600 cp in the existing waterflood and polymer-flood areas to more than 200,000 cp in the current undeveloped “immobile” area. This unique geological feature limits the application of chemical injection to the less-viscous areas of the field and calls for different methods for the heavier accumulations. As a first step to develop alternative technologies capable of recovering oil from heavier areas of the field not ideal for polymer flooding, a Cenovus-designed hot-water-injection pilot began implementation in June 2011. The hot-water-injection scheme was applied to a transition area in which dead-oil viscosity ranges from 3,000 cp to approximately 15,000 cp. It consisted of one horizontal producer supported by two horizontal hot-water injectors, with an injector/producer distance of 50 m for both injectors, and three vertical observation wells equipped to monitor pressure and temperature between one injector and the producer. The pilot was operated in three phases. The first phase consisted of a 6-month primary-production period to obtain a baseline of the pilot performance before hot-water injection. The second phase consisted of hot-water injection through the edge injectors. The third phase consisted of hot-water edge injection accompanied by hot-water circulation in the production well as a means to stimulate oil production. One of the features of this stage is the use of an insulated coiled tubing (ICT), which delivers hot water continuously to the toe of the producer and allows continuous stimulation and uninterrupted oil production. This paper describes the mechanical components of the pilot and discusses the results obtained with an emphasis on the hot-water-circulation process, which has proved to be very effective. Oil production increased from approximately 6 m3/d during the flood stage to more than 25 m3/d during the hot-water-circulation stage and has held relatively steady for more than 2 years. The data captured have been reconciled with analytical and reservoir-simulation models, and results suggest that the technology may help unlock some of the heavier oil accumulations in the field.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".