A workflow for estimating injection pressure limits for CO2 storage: A reservoir-geomechanical analysis of a candidate site in the German North Sea sector
Bibliographic record
Abstract
Geological carbon capture and storage (CCS) in saline formations is seen as a plausible short-term solution to reduce atmospheric carbon dioxide (CO₂) concentrations and mitigate climate change. Besides storage capacity, largely determined by pore space within a geological trap, the maximum allowable pressure in the storage formation represents a major limitation for geological CO₂ storage. This study, therefore, addresses the hydromechanical aspects of geological CO₂ storage by developing an integrated workflow to determine site-specific injection pressure limits and applying it to a potential storage site in the German North Sea sector. The workflow ensures consistency between reservoir flow and geomechanical models by automatically extracting near-wellbore geomechanical domains from the large-scale model. For a vertical well, the site-specific injection pressure limit is estimated at 17.9 MPa/km, governed by tensile failure in the storage formation. Within the cap rock, the limit increases to 28.6 MPa/km, providing a large margin of safety and enabling higher injection rates. A horizontal well configuration yields a slightly higher limit of 19.7 MPa/km, due to the larger well-reservoir contact area and improved pressure dissipation. The derived pressure limits are subsequently implemented in a large-scale dynamic simulation to verify workflow performance and assess formation integrity. Results indicate that injection rates of approximately 1.7 Mt CO₂ per year per vertical well can be sustained over 30 years, with reservoir overpressure and the corresponding stress states strongly dependent on the hydraulic setting of the reservoir. Importantly, injection-induced stresses and thus the probability of fracture formation decreases rapidly after CO₂ injection ends.
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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 | 0.001 |
| 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 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".