The Role of Effective Interfacial Tension in Alkaline/Surfactant/Polymer Flooding
Bibliographic record
Abstract
Abstract Ultra-low interfacial tension (IFT) between crude oil and brine is critical for successful enhanced oil recovery by alkaline/surfactant/polymer (ASP) flooding. With the right surfactant, this can be obtained at low and economic concentrations. However, maintaining low IFT during the displacement process is a serious challenge because of dilution and adsorption effects in the reservoir. Consequently, the effective in-situ IFT will change from the static equilibrium value, and have a corresponding influence on the oil displacement efficiency. The literature does not clearly address what level of static equilibrium IFT should be used to represent the in-situ IFT in order to predict oil recovery efficiency. The effect of changing IFT on the in-situ behaviour of given oil/brine systems was studied by carrying out IFT measurements with two surfactants using pre-equilibrated oil/brine/surfactant solutions. The effective equilibrated IFTs rose markedly as the oil volume proportion increased in the systems due to surfactant partitioning between the oil and aqueous phases. Displacement studies in reservoir and Berea cores reinforced the importance of understanding the role played by changes to the IFT at the oil/brine interface in displacing oil. The parameters varied were type and concentration of injected surfactant, slug size, and chase fluid. Through the use of theeffective IFT concept, the oil displacement efficiency showed good correlation with capillary number. The coreflood results further suggest that other factors, in addition to capillary number, may affect the displacement efficiency and should be included in the design of a cost-effective ASP flood. Introduction Enhanced oil recovery (EOR) with surfactants has become a more attractive tertiary recovery processes in recent years: new surfactant systems have been developed which lower the inputcosts to a reasonable level while maintaining good oil recovery. Experiments have shown that the ultra-low interfacial tension (IFT) of less than 10−3 mN/m can be obtained with less than 0.1 wt% surfactant concentration. 1 However, the effect of dilution of surfactant solution upon injection into the reservoir should be explored. Moreover, it should be established that the IFTs obtained in oil/brine/surfactant systems after rigorous equilibration procedures in the laboratory can indeed be achieved in situ when the surfactant solution contacts the entrapped oil ganglia in porous media. 2 How can the in-situ IFT be determined? There are few works in the literature that discuss this. In surfactant flooding, in-situ IFT is governed by several factors:reservoirs conditions;phase behaviour of surfactant between trapped oil and brine;degree of surfactant dilution; andsurfactant adsorption onto the rock surface. These factors make determining the in-situ IFT extremely difficult. Consequently, it is difficult to obtain a clear consensus about how IFT changes under reservoir conditions. However, one can be sure that the effective equilibrated interfacial tension is higher than the IFT obtained from laboratory equilibrium measurements due to loss of surfactant. Laboratory and field studies on oil displacement efficiencyby ASP flooding have been reported in the literature. 3, 5 Ideally, oil displacement by surfactant flooding approaches miscibility if the interfacial tension between the trapped crude oil and its associated brine is ultra-low.
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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 | 0.001 |
| 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 | 0.001 |
| 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 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".