Carbon dioxide storage in depleted gas reservoirs in northeastern Alberta: Prioritizing CO2 storage sites within a CCS value chain framework
Bibliographic record
Abstract
• Depleted shallow gas reservoirs in Alberta oilsands area offer promising CO 2 storage potential. • Prioritizing CO 2 storage sites by capacity, containment, injectivity, and spatial constraints. • High-potential storage zones recognized, informing regional carbon management strategies. • Shallow reservoirs in three favorable field clusters offer about 1.4 Gt CO 2 storage potential. Thousands of depleted shallow gas reservoirs in northeast Alberta offer a promising CO₂ storage complements to deep saline aquifers, supporting carbon removal in the oilsands region. This study presents a three-step framework to evaluate their suitability: a) initial screening to ensure sufficient capacity and injectivity, and containment, b) multi-criteria ranking to identify the most strategic candidates, and c) source–sink (S–S) optimization to integrate spatial and economic constraints within a carbon capture and storage (CCS) value chain framework, enabling the prioritization of optimal storage sites. From an initial inventory of 4694 depleted pools, 874 reservoirs with a combined capacity of 1518 Mt CO₂ were shortlisted. These were aggregated into fields and further integrated into four distinct trends based on geological and engineering characteristics within a CCS value chain framework. The Lower Cretaceous Kirby–Leming rend emerged as the most favorable, with capacity of 772 Mt CO 2 , strong injectivity, and economic viability. The Resdeln–Duncan trend followed closely, having a storage capacity of 366 Mt CO 2 , offering similar geological advantages but located farther from proposed pipelines. The Craigend–Lindbergh trend, while less optimal geologically with smaller capacity of 227 Mt CO 2 storage, aligns well with the planned Oil Sands Pathways Alliance CO₂ hub, making it a strategic complementary site. In contrast, the Devonian carbonate reservoirs in the Granor–Ukalta trend ranked lowest due to poor injectivity, long transport distances and lower capacity of 154 Mt. Altogether, the top three trends offer nearly 1400 Mt of storage potential. This study pinpoints high-potential CO₂ storage zones, providing insights for regional carbon management strategies. Integrating shallow gas reservoirs into Alberta’s CCS infrastructure could accelerate near-term carbon removal while reinforcing long-term net-zero objectives.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".