Alkaline/Surfactant Flood Potential in Western Canadian Heavy Oil Reservoirs
Bibliographic record
Abstract
Abstract For heavy oil reservoirs (with oil viscosities ranging from 1,000 to more than 10,000 mPa-s), primary production and waterflood can only recover 5 to 10% initial oil-in-place (IOIP) due to the unfavourable mobility ratio of the water phase to the oil phase. Heavy oils usually have a relatively high content of organic acids, which can be neutralized by alkalis to form in-situ surfactants. With the assistance of these in-situ surfactants, an oil-in-water emulsion with a much lower viscosity than heavy oil can be generated. In this way, the heavy oil is entrained in the water phase and produced out of the reservoir. An initial study was carried out to evaluate the feasibility of alkaline/surfactant (A/S) flooding for western Canadian heavy oil reservoirs. The integrated approach included extensive emulsification tests, oil/brine interfacial tension measurements, viscosity measurements, and sandpack flood tests. The experimental results showed that the dynamic interfacial tension of oil/water can be lowered to an ultralow level (< 0.01 dyne/cm) by an alkaline solution and a very dilute concentration of surfactant, leading to easy emulsification of heavy oil in formation brine under slight interfacial disturbance. A series of sandpack flood tests were carried out to investigate the recovery performance of A/S flooding for five western Canadian heavy oils with viscosities ranging from 650 to 18,000 mPa-s at 22°C. Tertiary oil recoveries in sandpack flood tests were between 20 to 30% IOIP. The results of these sandpack flood tests suggest that A/S flooding is a promising enhanced oil recovery process for thin heavy oil reservoirs, in which thermal processes are not suitable.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".