New Developement of Cationic Surfactant Formulations for Foam Assisted CO2-EOR in Carbonates Formations
Bibliographic record
Abstract
Abstract While the global oil demand is set to increase, reducing CO2 emissions is one of the great challenges to be tackled in the coming decades. CO2-EOR has a lot of potential within a CCUS strategy, but the low gas viscosity induces limited sweep efficiency, resulting in poor storage capacity, especially in heterogeneous carbonates formations. CO2-Foams are used to alleviate such drawbacks but special care must be taken with carbonates due to water/surfactants-rock interactions. A new cationic surfactant formulation is designed through a high throughput screening procedure accounting for solubility at high temperature (80°C), high salinity (160g/L TDS) and high hardness (R+=0.3), increased foam half-life time (at 120bar), reduced adsorption on carbonate powder and finally Ottawa sandpack flood tests (non-reactive transport). Core flooding experiments are performed on Indiana Limestone cores at 130bar and 40°C, prior targeting higher temperature. Dense supercritical CO2 is co-injected along with the surfactant formulation at the core inlet to ensure foam generation inside the rock and apparent CO2 viscosity is measured to assess the foam performance of each formulation. In this work several surfactant families are tested, among which: (1) anionic surfactants formulation optimized for their performances in sandstones, (2) switchable cationic surfactant (tertiary amine ethoxylate), (3) cationic surfactant, and (4) optimized cationic surfactant formulation. Solubility of the optimized formulation is found to be excellent in all considered brine (up to high salinity and hardness) and at high temperature; low static is obtained on the carbonate minerals (99% calcite) and bulk foam half-life time with supercritical CO2 (40°C/120bar) exceeds 24h. As a first demonstration step, foaming performance of each surfactant formulation is assessed through coreflood tests using intermediate salinity level water. The foam shear-thinning rheological behavior is obtained for velocities representative of near wellbore to in-depth reservoir conditions (from 5ft/day up to 50ft/day). Apparent viscosities are found to be very good, about dozens of centipoises for the lowest velocities. A technical challenges with carbonates lies in fluid/rock reactivity. The increase of divalent ions concentration in brine generally impairs both solubility and foaming ability of surfactant formulations. Here the use of the selected cationic surfactants less sensitive to divalent cations and allows both low adsorption on carbonate rocks and good foaming performance. A highly promising foaming cationic formulation, compliant with dense CO2 and carbonates, has been designed and thoroughly tested. Results obtained bring new opportunities for the CO2-foam process applied to carbonate formations within an EOR+/CCUS strategy.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".