Reservoir modeling for Wabamun lake sequestration project
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Bibliographic record
Abstract
Abstract A study, entitled “Wabamun Lake Sequestration Project” or “ WASP ,” was performed to evaluate large‐scale CO 2 storage opportunities in the Wabamun area including potential risks. The project examined the feasibility of storing 20 megatons (Mt) of CO 2 per year over 50 years. This scale is one order of magnitude larger than the typical benchmark (1 Mt/year) used in academic research and commercial projects that are currently in place or under review. The study was conducted by a group of researchers from several universities as well as industry consultants. This study presents an overview of the reservoir modeling part of this study, which the authors were responsible for. The main objectives of the reservoir modeling for WASP project were as follows: (1) estimation of storage capacity (traditionally, this value is projected based on the available pore space, but we have an additional practical consideration: the maximum amount one can inject within short period of time [~50 years] and within a localized injection area [~30 km × 90 km]); (2) investigation of CO 2 plume movement and pressure distribution during and after injection including the effect of formation dip angle on the plume shape and its migration; (3) investigation of the long‐term fate of injection associated with free phase CO 2 (risks of leakage) and aquifer pressurization (possible geomechanical changes and related phenomena); (4) investigation of the phase behavior of H 2 S initially available and dissolved in brine during CO 2 sequestration process. The WASP reservoir modeling study mentioned above led to a few important findings. The most important one is that, when CO 2 is being injected into a sour aquifer, initially dissolved H 2 S will release into the expanding CO 2 plume and accumulate at the leading edge of the plume. Also, the large‐scale injection scheme (20 Mt/year), which requires multi well injectors, provides very different pressure response compared to a one well (1 Mt/year) scenario.
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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 | 0.000 | 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 | 0.001 |
| 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 it