A New Mechanistic Model for Wettability-Altering Surfactant Floods in Carbonates
Bibliographic record
Abstract
Summary Surfactants and low-salinity brines have been shown to be effective for enhanced oil recovery in carbonate rocks through wettability alteration (WA). Oil wettability of carbonates is ascribed to the adsorbed organic acid components in oil. The removal of the adsorbed acids leads to WA. Previous experiments with wettability-altering surfactants have shown the following: WA is a slow process; acid removal is irreversible in most cases; surfactants can access the rock surface in water-wet regions and at three-phase contact lines rather than the entire rock surface; surfactant molecules become inactive after interactions with acids. Existing models/simulators do not incorporate the aforementioned observations. In this work, a multiphase, multicomponent, finite-difference reservoir simulator incorporating a new mechanistic model for WA was developed. The model captures the key physicochemical reactions between adsorbed acids and surfactant molecules and honors the four experimental evidences. The model was first tested at the core scale. The simulation results demonstrated that the model can accurately predict waterflood performance in rocks with various wettability. It can also effectively account for the influence of injection rates in surfactant flood experiments. The effectiveness of the surfactant, controlled by an interaction constant in the model, was found to be a dominant factor. The model was also tested for field-scale pilot tests. The results revealed that total quantity of chemicals injected and the injection rate have a more pronounced effect on oil recovery compared to the timing of surfactant treatment and the concentration of surfactant slug.
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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".