Polymer Screening for the Hebron Field, Offshore Eastern Canada - Facing High Salinity Brines
Bibliographic record
Abstract
Summary The Hebron Project is the fourth major offshore development in the province of Newfoundland and Labrador, with an estimated 2620 MBO in place and 800 MBO recoverable. Hebron Field oil and reservoir properties are similar to previous successful offshore polymer flooding projects. However, the formation water salinity, which is greater than 60,000 ppm, is higher than offshore field analogues used for the EOR screening. This paper reports viscosity variations due to salinity and temperature changes observed in two commercial, partially-hydrolyzed polyacrylamides, FP-3430S and FP-5115, and the biopolymer Guar Gum, using offshore Eastern Canada seawater and synthetic formation water brine. FP-3430S and FP-5115 showed similar viscosity responses in relation to salinity and temperature changes compared with Guar Gum, which was more salinity tolerant over the range of salinity investigated, but showed a greater viscosity decrease at salinity values higher than seawater. Guar Gum was also found to be more unstable at temperatures higher than 62°C. FP-3430S showed a higher viscosifying power, requiring less polymer mass to reach the same viscosity values even in different brine salinities. This indicates that FP-3430S is the most suitable for use with the Hebron Field brines, according to the conditions evaluated in this study.
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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 | 0.000 | 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) | 0.001 | 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".