Evaluation of Polymer-Assisted Carbonated Water Injection in Sandstone Reservoir: Absorption Kinetics, Rheology, and Oil Recovery Results
Bibliographic record
Abstract
The efficacy of carbonated water injection (CWI) is associated with weak CO 2 absorption in water, and the resulting CWI does not meet the requirements of controlled CO 2 mobility and enhanced oil recovery (EOR). High molecular weight oilfield polymer, e.g., polyacrylamide (PAM), is water-soluble and often used in water shut-off and mobility control applications. Thus, in this study, PAM, with concentrations (0.5, 1, and 2 g/L), as a viscosifier is used to improve the CO 2 absorption capacity of water for possible implementation in CWI applications. PAM with intermediate concentration (1 g/L) was favorable for enhanced CO 2 absorption with a retention period of 4 days in water. With high PAM concentration (2.0 g/L), CO 2 absorption reduced and gas in the form of globules moderately absorbed in the upper layers of P-1 solution, resulting in a significant amount of aqueous phase left unabsorbed by CO 2 . At high PAM concentration, enough number of PAM chains were available to interact with CO 2 and, as a result, solution received premature gelling that resisted further entry of CO 2 . The effect of stirring on CO 2 absorption showed that the rate of stirring increases the amount of CO 2 absorbed in P-1 solution. These observations were supported by rheological data which showed that CO 2 absorption reduced the viscosity of the P-1 solution, and the decrease in viscosity is directly proportional to the amount of CO 2 absorbed. Finally, oil recovery experiments were performed using P-1 solution with and without CO 2 and compared with water. The oil recovery was found to be higher for P-1 solution prepared with 600 rpm. Thus, this study highlights the application of relatively common oilfield polymer PAM (⩽ 1 g/L) for enhanced CO 2 absorption and improved oil recovery than conventional CWI, which recommends use of polymer-enhanced carbonated water injection (PE-CWI) in oil and gas industry.
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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".