Relative Permeability Characteristics for Supercritical CO2 Displacing Water in a Variety of Potential Sequestration Zones in the Western Canada Sedimentary Basin
Bibliographic record
Abstract
Abstract Sequestration in deep underground formations of large amounts of CO2, captured from large stationary sources, such as power plants, oil upgraders and refineries, is one method that is under consideration for reducing greenhouse gas emissions to the atmosphere in both Canada and United States. In hydrocarbon-producing regions, such as Texas in the United States and Alberta in Canada, CO2 geological sequestration is likely to first occur in depleted or abandoned oil and gas reservoirs. However, in many regions, including oil and gas producing areas, this is insufficient because either the sequestration capacity of oil and gas reservoirs is lower than the amount of CO2 emissions from large stationary sources, or because this capacity is not available until the reservoirs are depleted. Deep saline aquifers provide a very large capacity for CO2 sequestration that is immediately accessible, and they are found in all sedimentary basins in the North American mid-continent. Proper understanding of the relative-permeability character of such systems is essential in ascertaining CO2 injectivity and migration, and in assessing the suitability and safety of prospective CO2 sequestration sites. This paper reviews the experimental protocol and presents detailed water-CO2 relative permeability data for three sandstone and three carbonate formations in the Wabamun Lake area southwest of Edmonton in Alberta, western Canada, where four major coal-fired power plants which produce large volumes of CO2 are located. These formations are in general representative of the in-situ temperature, pressure, salinity, porosity and intercrystalline permeability characteristics of deep saline aquifers in on-shore North American sedimentary basins. The data will allow detailed numerical simulations of CO2 injection and sequestration processes both at this specific location, and for similar operations planned elsewhere and around the world.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".