Design Approach and Early Field Performance for a Solvent-Assisted SAGD Pilot at Cold Lake, Canada
Bibliographic record
Abstract
Abstract ExxonMobil and its affiliate Imperial Oil Resources are currently operating a Solvent-Assisted Steam-Assisted Gravity Drainage (SA-SAGD) experimental pilot plant at Cold Lake, Canada. During pilot operation, up to 20 percent by volume of a light hydrocarbon solvent will be injected with dry steam in a dual horizontal well SAGD configuration. The pilot scope consists of two horizontal well pairs (four wells total), six observation wells, associated steam and solvent injection facilities, artificial lift, and dedicated production measurement and testing facilities. Previous experimental and computer modeling work completed by the Alberta Research Council (ARC) (Nasr, 2003), Imperial Oil Resources, and ExxonMobil indicates that the addition of solvent to the dry steam increases bitumen production rates and decreases the steam oil ratio (SOR) relative to conventional SAGD processes. A key objective of this pilot is to safely collect high-quality field data to support these findings and quantify process improvement. This paper will focus on the pilot design approach taken to ensure that the multi-year pilot is successful as well as highlight early pilot performance and operation. Specific design aspects which will be discussed include the choice for the pilot location, the use of detailed geologic models to design and place the horizontal wells, and solvent measurements. Early field results are consistent with expectations. However, longer term operation is required to make a more quantitative assessment. In addition, the pilot operation has demonstrated excellent control of injection pressure, which is critical to the application of this technology in settings with bottom water or top gas.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".