Risk‐based area of review estimation in overpressured reservoirs to support injection well storage facility permit requirements for CO<sub>2</sub> storage projects
Bibliographic record
Abstract
Abstract This paper presents a workflow for delineating a risk‐based area of review (AOR) to support a US Environmental Protection Agency (EPA) Class VI permit for a carbon dioxide (CO2) storage project. The approach combines semianalytical solutions for estimating formation fluid leakage through a hypothetical leaky wellbore with the results of physics‐based numerical reservoir simulations. The workflow is demonstrated using a case study for a hypothetical 180,000‐metric‐ton‐per‐year storage project located in the Plains CO2 Reduction (PCOR) Partnership region, which includes all or part of 10 states in the United States and four Canadian provinces. Under the scenario where the leaky wellbore is open to a saline aquifer (thief zone) between the overlying seal (cap rock) and the underground sources of drinking water (USDW), the risk‐based AOR is no larger than the areal extent of the CO2 plume in the storage reservoir because the pressure buildup in the storage reservoir beyond the CO2 plume is insufficient to drive formation fluids up a hypothetical leaky wellbore into the USDW. However, even under the conservative assumption that the leaky wellbore is not open to a thief zone, the incremental leakage beyond the areal extent of the CO2 plume is less than 400 m3 over 20 years. The approach outlined in this paper is designed to be protective of USDWs and comply with the Safe Drinking Water Act requirements and provisions for the EPA Class VI Underground Injection Control (UIC) Program (Class VI Rule) and North Dakota Administrative Code Chapter 43‐05‐01. © 2021 Society of Chemical Industry and John Wiley & Sons, Ltd.
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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 | 0.008 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".