Feasibility study of CO2-based cyclic solvent injection and polymer flooding alternation process to enhance heavy oil recovery
Bibliographic record
Abstract
Heavy oil reservoirs possess substantial reserves exceeding 600 billion tons. However, the recovery factor is estimated around 11 % due to high oil viscosity, indicating substantial potential for further enhancement of oil recovery. Traditional enhancing heavy oil recovery (EHOR) technologies, such as thermal recovery, are often constrained by high energy consumption and significant CO 2 emissions. To achieve green and significant improvements in heavy oil recovery, this study proposes an innovative hybrid approach: CO 2 -based cyclic solvent injection (CO 2 -CSI) and polymer flooding alternation process. Five experimental groups were conducted using 1D sand-pack model to evaluate EHOR potential and operational parameters. A maximum oil recovery of 70.72 % was achieved when the final CO₂-CSI cycle was alternated with 1000 ppm polymer flooding. The enhanced performance is attributed to two synergistic mechanisms: CO 2 -CSI phase effectively mobilizes and produces heavy oil while reducing the residual oil viscosity; The alternating polymer flooding facilitates the formation of oil bank for CO 2 -CSI, which enhances the efficiency of subsequent CO 2 -CSI cycles. Furthermore, a novel ‘dual-mobility-ratio-control’ concept is introduced and validated as a key mechanism for optimizing mobility ratios in both displacing and displaced phases. Economic analysis indicated that the new proposed technology exhibited excellent economic benefits, reducing material costs by over 70 %. The EHOR technique proposed in this study demonstrates high efficiency, cost-effectiveness, and low carbon emissions, offering new insights and guidance for the development of heavy oil reservoirs. • CO 2 -CSI and polymer flooding alternation process is proposed. • CSI process, utilizing CO 2 as solvent, is effectively combined with polymer flooding. • “Back and forth” movement of foamy oil is weakened by polymer flooding. • The concept of “dual mobility ratio control” is introduced for the first time. • The oil recovery factor is up to 55 % higher than that of conventional CO2-CSI.
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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".