Optimized Surfactant–Polymer Flooding for Western Canadian Heavy Oils
Bibliographic record
Abstract
Abstract Chemical flooding for Western Canadian heavy oil reservoirs has gained popularity in recent years because of its satisfactory recovery efficiency and low facility cost. Formation brines in most of these reservoirs have extremely high salinity and hardness. Addition of alkali is prone to causing severe precipitation/scaling problems in both the injection/formation brinesand production facilities. As well, breaking of the emulsion generated during oil production is problematic in the presence of alkali. In order to overcome the operation/handling issues associated with alkali, an alkali-free surfactant–polymer (SP) flooding EOR method needs to be developed and evaluated. In this work, several amphoteric surfactants, which exhibit higher salinity- and hardness-resistance than common anionic surfactants, were evaluated in combination with the polymer polyacrylamide. For the crude heavy oil and brine studied, a fairly low interfacial tension (IFT) of 0.012 dyne/cm was measured at 0.1 wt% of surfactant concentration. Emulsification tests showed that the surfactant could easily generate oil-in-water emulsion in the heavy oil–brine system, while it was more difficult to form emulsion with the SP system due to its higher viscosity. Addition of the surfactant helped to slightly increase the polymer solution's viscosity, since the surfactant itself is a viscoelastic fluid. The SP system exhibited long-term stability with consistent viscosity and IFT, whereas an alkaline–surfactant–polymer (ASP) system had increased viscosity for the first 15 days due to solids precipitation in the brine and possible polymer hydrolysis. To compare the recovery efficiency by different chemical injectants, three coreflood tests were conducted using P, SP, or ASP systems. ASP flooding had the highest enhanced oil recovery (chemical injection + extended waterflood] of 25.17% original oil in place (OOIP), followed by SP flooding (24.38% OOIP) and P flooding (20.23% OOIP). However, the potential for operational problems evident with the use of alkali might restrict the application of ASP flooding. Varied oil recoveries at the chemical injection and EWF stages, as well as pressure drop variation (resistance factor), indicated that different recovery mechanisms were involved in each chemical flood. Given its satisfactory recovery results and potential to avoid operational problems, with careful optimization, SP flooding presents a promising method for heavy oil enhanced oil recovery, particularly for Western Canadian heavy oil reservoirs.
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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) | 0.001 | 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".