Experimental Evaluation of CO2-Soluble Nonionic Surfactants for Wettability Alteration to Intermediate CO2-Oil Wet during Immiscible Gas Injection
Bibliographic record
Abstract
Summary The change in wettability of limestone reservoirs from oil-wet toward gas-wet can enhance crude oil production during immiscible CO2 injection. Therefore, in this research, we investigated the impact of wettability alteration to CO2-wet on oil recovery factor via dissolution of fluorine-free, CO2-philic, nonionic surfactants such as C4(PO)6 and C41H83O19 in CO2. Based on the cloudpoint measurements, the dissolution pressures of nonionic surfactants in supercritical CO2 ranged between 2,100 psi and 2,700 psi (below the reservoir pressure, i.e., 3,000 psi) at reservoir temperature, 65°C; these pressures are commensurate with CO2-enhanced oil recovery (EOR) pressures. Also, the C4(PO)6 and C41H83O19 can reduce the CO2-oil interfacial tension (IFT). Moreover, the CO2/C4(PO)6 and C41H83O19 solutions can change the limestone wettability from strongly oil-wet (Θ ~ 20o) to intermediate CO2/oil-wet (Θ = 95o and 110o) at reservoir conditions. The relative permeability curves also confirmed it by changing the curvature to the left and decreasing the residual oil saturation in both cases of CO2/C4(PO)6 and C41H83O19 solutions. The 20.8% and 13.1% additional oil recoveries were achieved during the 30,000 ppm CO2/C4(PO)6 and C41H83O19 solution scenarios, respectively, relative to the pure CO2 injection scenario. These nonionic surfactants are not able to make CO2-in-oil foam; therefore, wettability alteration and perhaps IFT reduction are the dominant mechanisms of EOR induced by the dissolution of nonionic surfactants in CO2, instead of CO2 mobility control. Consequently, the dissolution of fluorine-free, oxygenated, CO2-philic, nonionic surfactants (such as C4(PO)6 and C41H83O19) in CO2 at 30,000 ppm concentration can be a well-qualified candidate for altering the limestone wettability to intermediate CO2-oil-wet during the immiscible CO2 injection.
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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 | 0.001 | 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 | 0.001 |
| 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 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".