A coupled geomechanical reservoir simulation analysis of carbon dioxide storage in a saline aquifer in the Ohio River Valley
Bibliographic record
Abstract
Abstract With almost 200 coal-burning power plants in the region, the Ohio River Valley is an important region to evaluate potential formations for carbon dioxide (CO2) storage. In this study, we consider whether injection-induced stress changes affect the viability of the Rose Run Sandstone, considered as a potential effective storage unit. Our study uses a coupled geomechanical and reservoir simulator that couples fluid flow to induced stress and strain in all the significant stratigraphic units from the surface to the crystalline basement. The pressure and stress variations were modeled during CO2 injection, focusing on injection from a single well. The model uses a constant pressure condition on the boundary of the system. Both reservoir and surface deformation were simulated, and the possibility of reaching shear failure in the reservoir was tested. Carbon dioxide injection in the Rose Run Sandstone aquifer is not likely to cause any significant surface deformation. To consider the potential of increasing injectivity, simulation of a static fracture with a half-length of 300 m (984.3 ft) was considered. As the modeling shows that, with constant injection rate, the fracture can propagate beyond the propped length, a dynamic fracture propagation was also studied. This was achieved by allowing the fracture to grow as a function of a propagation criteria based on effective stress. Because of the favorable stress state of the Rose Run Sandstone, the propagation is primarily in the lateral direction, and no upward fracture propagation through the cap rock has been observed in the model. Finally, we demonstrate that dynamic fracture propagation significantly increases the possible injection rates, and its modeling is useful for determining optimal injection rates.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".