The role of injection rate in enhancing $${\textrm{CO}}_2$$ capillary trapping in saline aquifer systems
Bibliographic record
Abstract
As the energy industry transitions toward net-zero emissions, underground carbon dioxide ( $$\textrm{CO}_2$$ ) storage plays a crucial role in mitigating global warming caused by anthropogenic $$\textrm{CO}_{2}$$ emissions. Capillary trapping is considered one of the most promising mechanisms for $$\textrm{CO}_2$$ storage in saline aquifer systems. It is essential for securely immobilizing $$\textrm{CO}_2$$ in porous rock formations, improving the long-term stability of geological storage. The lack of understanding of factors affecting the contribution of capillary trapping in sequestration may result in only partial achievement of technical and financial objectives. In this study, the mutual relationship between injection rates, initial saturation of $$\textrm{CO}_2$$ , and capillary trapping capacity was studied by performing displacement experiments on a micromodel representing a heterogeneous sandstone aquifer. The brine-alternating- $$\textrm{CO}_2$$ (BAC) technique was applied under varying injection conditions of brine and proxy supercritical $$\textrm{CO}_2$$ ( $${\textrm{ScCO}}_2$$ ) into the micromodel. In this study, it was observed that large clusters of trapped $$\textrm{CO}_2$$ were developed due to the dominance of capillary forces at lower injection rates of brine, resulting in a trapped $$\textrm{ScCO}_2$$ saturation of 0.62. However, the saturation of trapped $${\textrm{proxyScCO}}_2$$ was decreased to 0.37 due to the increasing influence of viscous forces at higher injection rates. This study highlights the crucial role of capillary and viscous forces during BAC injection in heterogeneous sandstone reservoirs and provides a guideline for laboratory-scale $$\textrm{ScCO}_2$$ sequestration studies.
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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".