Visualization of Interfacial Interactions of Crude Oil-CO2 Systems under Reservoir Conditions
Bibliographic record
Abstract
Abstract In this paper, an experimental technique is developed to study the interfacial interactions of the crude oil-CO2 systems under reservoir conditions. By using the axisymmetric drop shape analysis (ADSA) for the pendant drop case, this new technique makes it possible to measure the interfacial tension (IFT) and to visualize the interfacial interactions between crude oil and CO2 at high pressures and elevated temperatures. The major component of this experimental set-up is a see-through windowed high-pressure cell. A number of important physical phenomena have been observed when the crude oil is made in contact with CO2. They include oil swelling, lightends extraction, initial turbulent mixing, skin layer, oil drop movement, wettability alteration, asphaltene precipitation, and bubbling at the crude oil-CO2 interface. In particular, the lightends extraction, initial turbulent mixing and wettability alteration are the major characteristics of the CO2 flooding processes. It is also found that there always exists a constant low equilibrium IFT as long as the pressure is higher than a threshold value. No ultra low or zero IFT between crude oil and CO2 is found, regardless of the operating pressures and temperatures. Therefore, the measured constant low IFT and the observed interfacial interactions show that only partial miscibility between crude oil and CO2 can be achieved for most reservoirs. In addition, it is anticipated that wettability alteration may have significant effects on the ultimate oil recovery and CO2 sequestration.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".