Effect of Oil/Brine Ratio on Interfacial Tension in Surfactant Flooding
Bibliographic record
Abstract
Abstract The difficulty of determining the effective interfacial tension (IFT) in porous media limits the modeling and prediction of surfactant flood performance. Surfactant dilution, adsorption and partitioning - occurring as the aqueous solution is injected into the reservoir and as it contacts the oil - will raise the effective in-situ IFT from the nominal value as measured traditionally. This change will have a corresponding influence on the oil displacement efficiency. A laboratory study of the interfacial tension behaviour of oil/surfactant-brine systems was conducted. The effective equilibrated oil-surfactant IFT - that is, the IFT closest to that actually produced by partitioning effects in the porous medium - was found to change greatly from the nominal values. When the ratio of oil to brine reached 40:60, the effective equilibrated IFT for the systems approached the original value of crude oil/brine without surfactant, apparently losing much of the advantage provided by a surfactant flood. However, the interfacial tensions between equilibrated oils and a fresh surfactant solution indicate that injecting additional chemicals would maintain the IFT at a reasonably low level. This was confirmed with visual micromodel floods: oil displacement efficiency was poor when equilibrated surfactant- brine solution was injected into a model containing equilibrated oil, and then greatly improved by injecting fresh surfactant solution. These findings are important for progress towards designing successful chemical floods. Introduction Enhanced oil recovery (EOR) by surfactant flooding has become more attractive in recent years. Low interfacial tension at low surfactant concentrations, and acceptable adsorption levels are considered to be important design parameters in optimising chemical systems for recovering trapped oil from petroleum reservoirs.[1,2] Ultra-low interfacial tensions of less than 10−3 mN/m have been reported with less than 0.1 wt% surfactant concentration measured by the traditional spinning drop method.[3] However, interfacial tension can be very difficult to accurately extrapolate from laboratory conditions to reservoir-like conditions. In a surfactant flood, the best surfactant performance depends on the characteristics of crude oil and brine, reservoir conditions, and several other stringent requirements, such as low retention, compatibility, and thermal and aqueous stability. Surfactant retention is due in part to adsorption on the rock surfaces, but other loss mechanisms Because there are limitations to studying the effect on interfacial tension of dilution, adsorption and partitioning of surfactant solution upon injection into the reservoir, it is not surprising that many studies use the IFT without considering adsorption and partitioning to predict surfactant flood performance. The traditional method of measuring ultra-low interfacial tensions (down to 10−3 mN/m) between two fluid phases is the spinning drop technique. In this test, a small drop of oil, of which the volume is less than 0.1 cm3, is injected inside a thin tube filled with a surfactant solution (approximate volume 1 cm3), and the tube is rotated at a high speed. The interfacial tension of the oil against water is able to be calculated from the angular speed of the tube and the diameter of the oil drop. The interfacial tension is obtained using a 0.1 oil-to-water ratio.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".