Screening Surfactants for Application in SAGD – Including a Steam-phase Coreflood Test
Bibliographic record
Abstract
Abstract This research sought to determine whether surfactants and other steam additives can further improve oil recoveries in steam-assisted gravity drainage (SAGD), and to identify plausible mechanisms. It involved extensive experimental study and method development to screen the surfactants suitable for high temperature application and to evaluate incremental improvements in bitumen recovery using surfactants in the gas phase. Formulations of several surfactants were prepared to optimize their properties (e.g., cost, performance, partitioning, water solubility). The types of surfactants selected for this study were sulfonates and pyrrolidones. These surfactants were pre-screened according to thermal stability in water, interfacial tension (IFT), contact angle, and formation water compatibility. The selected surfactants were tested using the specially designed steam soak apparatus to evaluate the transport of surfactants in the steam phase to the gas/bitumen interface. Linear hot water and steam corefloods in different configurations were also performed to investigate the oil recovery mechanism associated with the use of high temperature surfactants. High-performance liquid chromatography (HPLC) was used to measure surfactant concentrations for thermal stability and coreflood testing. The steam-soak tests did reveal that combining N-octyl-2-pyrrolidone (NOP) with a sulfonate surfactant, alkyldiphenylethersulfonate (ADPES), could substantially improve oil recovery. This was dispite the fact that sulfonates are not volatile in steam. The hot-water corefloods showed an upward trend in oil recovery with an increase in the N-alkyl-2-pyrrolidone molecular weight and boiling point. The steam corefloods showed the highest recovery for surfactant mixture with 1000 mg/kg NOP and 500 mg/kg ADPES. The post-run core images showed cleaner sand indicating the incremental recovery from the use of surfactant mixture was being achieved by producing the residual oil from the steam chamber. NOP is miscible with bitumen, and is capable of dissolving asphaltenes. However, the viscosity data of oil treated with NOP suggests that viscosity reduction due to surfactant/additive addition is probably not the primary mechanism responsible for improved recoveries. Rather, it can be attributed more towards the IFT reduction, wettability alteration or surfactant dispersion of bitumen in water. No tight bitumen-in-water emulsions were produced in any of the tests.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".