A numerical analysis of background flow velocity effects on long-term post-injection migration of CO2 plumes in tilted storage aquifers
Bibliographic record
Abstract
Even though groundwater flow exists in many saline aquifers, very few studies have investigated its significance on the injected CO2 migration and trapping processes. Here, a numerical simulation approach is used to study the late post-injection migration and trapping of CO2 injected into a tilted aquifer. The analysis highlights that although the migration of the CO2 and its dissolution in brine is induced by buoyancy, the existence of background flow can further affect the plume velocity, convective dissolution, the dissolved CO2 flux and its distribution in the storage complex. Our analysis shows that the background flow removes the residual CO2, by dissolution, before the convective dissolution of the mobile part becomes dominant. The plume decelerates during its vertical migration by a factor of 6.5; then, its height increases with time to more than 15% as background flow velocity increases, hence reducing its rate of deceleration. However, when the plume reaches its maximum height, it migrates with a constant velocity. Greater background flow velocity not only allows the plume to migrate further, but it may hinder CO2 dissolution. This is because it can transport the dissolved CO2 underneath the plume for a long time, thus slowing down the interaction at the CO2-brine interface. The weak and strong background flows can impact the tendency of the dissolved CO2 to persist underneath the caprock. Our results indicate the existence of a critical background flow velocity which can control the distribution of the dissolved CO2 at the bottom of the aquifer, further away from the caprock. Document Type: Original article Cited as: Awag, M., Mackay, E., Ghanbari, S. A numerical analysis of background flow velocity effects on long-term post-injection migration of CO2 plumes in tilted storage aquifers. Advances in Geo-Energy Research, 2024, 11(2): 103-114. https://doi.org/10.46690/ager.2024.02.03
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| 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 teacher head, 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".