Exploring Pressure Interactions Between Geological CO2 Storage Projects in Alberta Using Analytical and Numerical Simulations
Bibliographic record
Abstract
Abstract Deep saline aquifers are considered as attractive hosts for geological CO2 storage (GCS). The Western Canada Sedimentary Basin (WCSB) comprises numerous saline aquifers. Depending on formation geochemistry, in-situ conditions, and petrophysical properties, each formation will have different storage capacity and efficiency. There are currently 25 proposed projects in the province of Alberta that, if they were all approved with pore space tenure, would inject large volumes of CO2 at relatively large rates into the WCSB. The goal of this study is to present characterizations of potential storage formations and examine the potential for interactions between proposed projects in proximity. We use numerical and analytical simulation to assess the evolution and interaction of pressure fields from proposed projects over time in the Wabamun Area CO2 Sequestration Project (WASP) region and infer how this affects cumulative storage capacity in the target formations. We compare the result from simple, relatively easy-to-use analytical tools against numerical simulation results to determine whether existing screening tools could accurately capture potential interactions between proximal projects. The results reveal that with increasing length of injection years, the radial extent of the CO2 pressure distribution increases as well. The analytical solution cannot accurately capture formation compressibility and variation in fluid properties, which leads to deviations from the simulated values. Nonetheless, these tools could serve as a quick method to identify areas of concern, and both can provide useful information about the likely extent of the pressure plume in a GCS project.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 | 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".