Assessing the Effect of Timing of Availability for Carbon Dioxide Storage in the Largest Oil and Gas Pools in the Alberta Basin: Description of Data and Methodology
Bibliographic record
Abstract
Carbon dioxide capture from large stationary sources and storage in geological media is a technologically-feasible mitigation measure for the reduction of anthropogenic emissions of CO2 to the atmosphere in response to climate change. Carbon dioxide (CO2) can be sequestered underground in oil and gas reservoirs, in deep saline aquifers, in uneconomic coal beds and in salt caverns. The Alberta Basin provides a very large capacity for CO2 storage in oil and gas reservoirs, along with significant capacity in deep saline formations and possible unmineable coal beds. Regional assessments of potential geological CO2 storage capacity have largely focused so far on estimating the total capacity that might be available within each type of reservoir. While deep saline formations are effectively able to accept CO2 immediately, the storage potential of other classes of candidate storage reservoirs, primarily oil and gas fields, is not fully available at present time. Capacity estimates to date have largely overlooked rates of depletion in these types of storage reservoirs and typically report the total estimated storage capacity that will be available upon depletion. However, CO2 storage will not (and cannot economically) begin until the recoverable oil and gas have been produced via traditional means. This report describes a reevaluation of the CO2 storage capacity and an assessment of the timing of availability of the oil and gas pools in the Alberta Basin with very large storage capacity (>5 MtCO2 each) that are being looked at as likely targets for early implementation of CO2 storage in the region. Over 36,000 non-commingled (i.e., single) oil and gas pools were examined with effective CO2 storage capacities being individually estimated. For each pool, the life expectancy was estimated based on a combination of production decline analysis constrained by the remaining recoverable reserves and an assessment of economic viability, yielding an estimated depletion date, or year that it will be available for CO2 storage. The modeling framework and assumptions used to assess the impact of the timing of CO2 storage resource availability on the region’s deployment of CCS technologies is also described. The purpose of this report is to describe the data and methodology for examining the carbon dioxide (CO2) storage capacity resource of a major hydrocarbon province incorporating estimated depletion dates for its oil and gas fields with the largest CO2 storage capacity. This allows the development of a projected timeline for CO2 storage availability across the basin and enables a more realistic examination of potential oil and gas field CO2 storage utilization by the region’s large CO2 point sources. The Alberta Basin of western Canada was selected for this initial examination as a representative mature basin, and the development of capacity and depletion date estimates for the 227 largest oil and gas pools (with a total storage capacity of 4.7 GtCO2) is described, along with the impact on source-reservoir pairing and resulting CO2 transport and storage economics. The analysis indicates that timing of storage resource availability has a significant impact on the mix of storage reservoirs selected for utilization at a given time, and further confirms the value that all available reservoir types offer, providing important insights regarding CO2 storage implementation to this and other major oil and gas basins throughout North America and the rest of the world. For CCS technologies to deploy successfully and offer a meaningful contribution to climate change mitigation, CO2 storage reservoirs must be available not only where needed (preferably co-located with or near large concentrations of CO2 sources or emissions centers) but also when needed. The timing of CO2 storage resource availability is therefore an important factor to consider when assessing the real opportunities for CCS deployment in a given region.
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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 | 0.014 | 0.003 |
| 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 | 0.000 |
| 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 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".