Performance of Secondary Carbonated Water Injection in Light Oil Systems
Bibliographic record
Abstract
In this study, the performance of secondary carbonated water injection (CWI) was investigated at various operating pressures (i.e., P = 0.7–10.3 MPa). Prior to CWI tests, CO 2 solubility in both brine and oil samples was measured using a high pressure visual cell. Next, through a series of flooding experiments, the effect of various operating conditions on the efficiency of CWI as a means of secondary oil recovery technique was investigated. Results showed that the ultimate oil recovery of secondary CWI can be increased by about 19% as compared to that of conventional water flooding (WF). It was also observed that in secondary CWI mode, an increase in operating pressure enhances the oil recovery, which is mainly attributed to higher CO 2 solubility in the injected brine. It was also found that the recovery factor (RF) substantially increases to the pressure of P = 5.9 MPa followed by slow growth until the pressure reaches P = 10.3 MPa. The same turning point of P = 5.9 MPa was also observed in the plot of CO 2 solubility in brine versus the operating pressure. Therefore, it was concluded that the value of CO 2 solubility in brine controls the efficiency of CWI process. Additionally, less recovery factor was obtained when temperature was increased from T = 25 to 40 °C. The same impact was observed when the carbonation level of the injected brine was reduced from CL = 100% to CL = 50%. However, it was seen that the carbonated water (CW) injection rate minimally affect the efficiency of the CWI. From the CO 2 storage point of view, the amount of CO 2 that was stored at the end of secondary CWI for different operating pressures was determined, and the values ranged from 23% to 36% of total injected CO 2 . Thus, it was concluded that CWI considerably has great potential to permanently store the injected CO 2 while significantly improving oil recovery in light oil systems.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".