Horizontal Wells for Enhanced CO<sub>2</sub> Storage in Saline Aquifers
Bibliographic record
Abstract
CO 2 sequestration in geological formations is crucial for mitigating the excessive greenhouse gas accumulation. Saline aquifers have been identified as the most appealing targets for the secure storage of CO 2 in the subsurface. However, limited effective capacity necessitates the implementation of enhanced injection methods to take the utmost advantage of the storage potential of the aquifers. This study investigates how horizontal wells enhance storage capacity and evaluates the impact of rock characteristics and project designs. Results show that replacing vertical injection wells with horizontal wells decreases bottom-hole pressure, improves pressure distribution, and delays CO 2 plume migration to the caprock. Longer horizontal wells offer more uniform pressure distribution, reducing fracturing risks and potential CO 2 leakage. However, excessive well length may not significantly enhance the storage capacity, questioning cost-effectiveness. Plume evolution studies indicate that longer well lengths improve lateral CO 2 distribution. High-permeability aquifers exhibit greater storage capacity with horizontal wells enhancing pressure distribution across all permeability ranges. In anisotropic aquifers, horizontal well efficiency is less pronounced, requiring longer lengths to surpass vertical well performance. It was also concluded that horizontal well utilization for enhancement purposes proved to have a more beneficial effect in aquifers with low permeabilities, smaller permeability ratios, and smaller thicknesses. This study highlights the importance of aquifer characteristics in optimizing CO 2 storage with horizontal wells.
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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".