Efficiency of Ionic Liquids as an Enhanced Oil Recovery Chemical: Simulation Approach
Bibliographic record
Abstract
A significant portion of crude oil remains in the reservoir after the application of conventional recovery. To meet the growing demand of energy, enhanced oil recovery (EOR) methods should be used efficiently to recover the extra amount of trapped crude oil after secondary water flooding. Surfactant flooding is one of the chemical EOR methods that can be implemented to recover oil from the remaining oil in place. Ionic liquids (ILs), which are salts with a melting point beneath 100 °C, were considered as a prospective alternative to the surfactant because of their superiority in different points. In this paper, three flooding experiments using Berea sandstone samples were conducted using IL solution (commercially called Ammoeng 102) in different scenarios to check its recovery efficiency. In the first scenario, a core sample was saturated with crude oil up to irreducible water saturation ( S wir ) and then secondary flooded with brine. IL solution was followed in tertiary flooding mode. The second scenario was implemented by injecting a slug of IL solution [0.4 pore volume (PV)] chased with brine in the secondary flooding stage. Continuous secondary flooding with IL solution from the beginning to the end of experiment was used to carry out the third scenario. The experimental runs were simulated using the surfactant flood model (SFM) available in CMG STARS software. All three scenarios were successfully simulated, and a good match was obtained for oil recovery, well bottom-hole pressure, and imbibition relative permeability curves. Both simulation and experimental results proved the superiority of secondary continuous IL solution flooding, providing the highest oil recovery [71% original oil in place (OOIP)] compared to 64% OOIP for the secondary flooding of 0.4 PV IL solution slug. Tertiary IL solution flooding consequent to secondary water flood was able to recover 48% OOIP. Experimental contact angle measurements and the shift in relative permeability curves indicate that wettability alteration toward more water-wet characteristics is the main recovery mechanism for ionic liquid flooding.
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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 | 0.000 | 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 | 0.000 |
| 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".