Potential Sinks for Geological Storage of CO2 in Saskatchewan
Bibliographic record
Abstract
Abstract Geological storage of CO2 in underground formations has the potential to be a major component of any viable solution to reduce atmospheric emissions of greenhouse gases. There are different options for long-term storage of CO2 in subsurface formations currently being considered by both government and industry. In general, the potential sinks for geological storage of CO2 include storage in depleted oil and gas reservoirs, deep saline aquifers, coal beds and salt caverns as well as injection for enhanced oil recovery (EOR). Suitable geological conditions as well as availability of CO2 sources provide a vast potential for geological storage of CO2 in Saskatchewan, Canada. This paper examines and summarizes the potential sinks for geological storage of CO2 in Saskatchewan. More specifically, the potential for CO2 storage in locations throughout Saskatchewan along with estimated storage capacities are discussed in detail. The possible sinks in each storage category have been identified through creation of a database of the available information, screening the sinks according to the appropriate criteria for each category, and evaluating their potential in terms of CO2 storage capacity. The database includes a significant number of oil pools in different stages of development, saline aquifers, and coal beds throughout Saskatchewan. Southeastern Saskatchewan contains deep saline aquifers in addition to several light and medium oil pools which offer a great potential for CO2 EOR and storage. Extensive unmined coal beds also exist in the southern and western parts of the province which can be possible candidates for coal bed methane production and CO2 sequestration. The identification and analysis of the potential sinks for geological storage of CO2 in Saskatchewan will contribute towards the development of integrated CCS infrastructure. This will also help to meet climate change mitigation objectives by reducing CO2 emissions through developing practical applications for geological storage of CO2.
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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 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".