Potential for environmental impact due to acid gas leakage from wellbores at EOR injection sites near Zama Lake, Alberta
Bibliographic record
Abstract
Abstract The potential for environmental impact from future leakage of toxic hydrogen sulfide (H2S) at an enhanced oil recovery (EOR) and acid gas sequestration site near Zama Lake, Alberta, is examined. Over 800 pinnacle reefs are potentially suitable for EOR by injection of acid gas. Leakage rate as a function of time through a reference wellbore is determined for various scenarios including leakage through the annulus of the wellbore and leakage through the central plug seal of the wellbore with an intact and failed wellbore casing. Potential plumes of H2S in the air and in shallow aquifers emanating from a single reference wellbore and from 350 wellbores are modeled. Leakage rates from the 350 wellbores are calculated from randomly sampled wellbore seal failure times, reservoir permeability, and initial amounts of acid gas, and from reference values of other reservoir parameters. Results indicate that for hundreds of years after injection, the entire Zama Lake area of 12 000 km2 could have lethal concentrations of H2S over each of the leaking wellbores. The shallow aquifers over the entire Zama area and over 30 kilometres in the direction of aquifer flow could be undesirably tainted with dissolved H2S. The entire Zama Lake area and hundreds of kilometres beyond could become uninhabitable for more than 1000 years after injection due to toxic plumes of H2S in the air and in shallow aquifers. This analysis has implications for the potential use of acid gas for EOR and for subsurface sequestration in general in areas with large numbers of abandoned wells. © 2012 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".