A Novel Injection Well String Design to Accelerate CO2 Dissolution in Deep Saline Sequestration
Bibliographic record
Abstract
Abstract Geological storage of carbon dioxide (CO2) is one of the proposed strategies for mitigation of global warming. The CO2 injected into saline formations has less density than that of the resident formation brine. The injected mobile supercritical phase migrates upward and spreads under the sealing rock, due to its buoyancy. While CO2 is in the free mobile phase, there is always a risk of leakage through natural and artificial pathways. Once CO2 is dissolved into brine, it cannot migrate upwards other than by diffusion; and, it can then be retained with a minimal risk of leakage. Therefore, solubility trapping could enable more secure storage. The objective of this study is the proposal of a CO2 injection well string to increase CO2 dissolution in brine and thereby reduce the risk of leakage of the injected CO2. The proposed well string configuration employs a tubing annulus system equipped with gas lift valves: The supercritical CO2 is injected through the annulus, and fresh brine is injected through the tubing. The designed flow rate of the injected CO2 through gas lift valves enhances dissolution of the CO2 into the injected brine. A simplified single-phase mechanistic model is developed, and analytical solutions of the governing equations are obtained. Using the developed model, the dissolution of CO2 into brine is characterized by governing dimensionless numbers, such as the Peclet and Sherwood numbers. Scaling relations are presented and can be used to investigate the mixing performance under various operating conditions.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".