Feasibility of Carbon Storage in Kirby Depleted Shallow Gas Fields: A Numerical and Statistical Analysis
Bibliographic record
Abstract
Abstract The current screening criteria excluded shallow formations (depth < 800 m) from the desirable CO2 geological storage sites. However, in the Athabasca oil sands area of northeast Alberta, shallow gas reservoirs have at least 500 Mt storage potential and are close to many large emitters in Alberta. This study uses Kirby gas fields as an example and examines the suitability of shallow gas reservoirs as CO2 storage sites from leaking risks associated with engineering aspects. First, the storage systems characterized by five parameters were built based on a statistical analysis of 210 gas pools in the Kirby field. Second, to capture uncertainties, 270 cases were simulated to represent the sealing-layer performances. The results were then analyzed statistically, where an information-entropy-based regression tree was generated to rank the relative importance of the parameters and leaking risk level. Third, the storage systems with multi-sealing layers were modeled to examine the effective drainage area, injectivity, and storage capacity under different drilling and injection schemes. Finally, the potential issues of carbon storage in depleted shallow gas fields were addressed. Our study suggests that the CO2 storage potential and carbon-neutral benefits of the shallow gas reservoir in the Athabasca oil sands area are underestimated for the low-carbon energy transition. The results found that the regression tree allows for screening parameters effectively for selecting storage sites from the shallow gas pools and revealed that the permeability of the sealing layers is more important than the seal thickness. For CO2 storage in shallow formations, the minimum requirements of the seal (especially for the caprock) under the safe injection pressure range are a permeability of less than 0.001 mD and a thickness higher than 35 m. Due to key characteristics of shallow gas reservoirs (high permeability and thin reservoir layers), the CO2 plume behaviors are significantly different from reported CO2 storages in desirable deep formations. The CO2 plume will spread rapidly in all directions of the reservoirs and reaches the maximum capacity quickly. A low well density of the CO2 injection network (< 0.39 wells/km2) is sufficient for CO2 storage in shallow depleted gas reservoirs. Compared to the single-layer injection scheme, the multi-layer injection can relieve the early leaking risks of the mid-sealing layers and increase the injection rate to nearly 1 Mt CO2 per year. The short project life resulting from the high injection rate and small storage capacity in each gas pool makes the CCS projects of shallow reservoirs in NE Alberta more suitable for transporting CO2 using tankers or repurposing the old pipelines nearby. It also makes the small (~64.7 E4m2) to medium gas reservoirs (259 E4m2) with excellent top seals the desirable candidates of CO2 storage for small companies when the carbon tax reaches $170/ton in 2030. A novel workflow with an effective assessment methodology for selecting CO2 storage sites from shallow gas pools has been proposed. The results can assist geoscientists in reducing uncertainty on the estimate of CO2 capacity storage and provide practical guidance on site selection for the pre-feasibility study of CO2 storage in shallow formations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.004 | 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".