CO<sub>2</sub> dissolution in the presence of background flow of deep saline aquifers
Bibliographic record
Abstract
Abstract We study the effect of background flow on the dissolution and transport of carbon dioxide (CO2) during geological storage in saline aquifers, and include the processes of diffusion, advection, and free convection. We develop a semianalytical model that captures the evolution of the dissolution in the absence of free convection. Using the semianalytical solution, we determine scaling relations for the steady rate of dissolution that follow either or depending on the value of Pe/R, where R represents the ratio of the extent of CO2 plume to the aquifer thickness and Pe is the Péclet number. Using direct numerical simulations, we provide detailed behavior of the convective mixing during the dissolution. We establish the criteria for forced and mixed (combined free and forced) convection in aquifers that is governed by the background flow. Accordingly, we provide the scaling relations and representing the forced and free convection asymptotes, respectively, where Ra is a Rayleigh number based on aquifer thickness. The results reveal that the background velocity can delay the onset of free convection and can alter the subsequent mixing. This phenomenon is more profound in the systems subject to strong background flows wherein horizontal component of the velocity field generated by background flow hinders the establishments of vertical component of the velocity field. Finally, by applying the proposed relations to several potential storage sites, we demonstrate the screening process in finding aquifers where the background flow exerts an important influence on the dissolution.
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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) | 0.000 | 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) | 0.000 | 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".