A Review of Phase Behavior Mechanisms of CO<sub>2</sub> EOR and Storage in Subsurface Formations
Bibliographic record
Abstract
The emissions of CO 2 have been recognized as the main cause of climate change. As an important strategy being used to reduce the CO 2 concentration in the atmosphere, carbon capture, utilization and storage (CCUS) has attracted significant attention in recent years. Geological formations, including depleted oil and gas reservoirs and saline aquifers, are popular CO 2 storage options. During the process of CO 2 storage in subsurface formations, the interactions between CO 2 and formation fluids must be considered as they could greatly affect the CO 2 trapping mechanisms and CO 2 storage capacity. In this paper, we give a brief review of the phase behavior mechanisms associated with CO 2 storage in subsurface formations. Two different CO 2 -storage strategies are considered in this paper: CO 2 storage in saline aquifers and CO 2 storage in oil reservoirs. Multiphase equilibria, including two-phase, three-phase, and four-phase equilibria, can be observed during CO 2 injection into underground formations. Both the experimental and modeling studies on the related phase behavior mechanisms are included in this Review. We also introduce some recently developed robust algorithms for the multiphase equilibria calculations, which could be essential for the design of the CO 2 storage process and prediction of CO 2 storage capacity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".