Enhanced hydrogeochemical baseline of a CO2 injection facility in southern Alberta, Canada
Bibliographic record
Abstract
Geological storage of CO 2 is anticipated to play a significant role in the management and reduction of greenhouse gas emissions. Monitoring of CO₂ injection facilities is essential to provide reassurance of the containment of the injected CO 2 . Here, we report results over six years (2018–2023) for a hydrogeological and geochemical (gas compositions, δ 13 C CH4, δ 13 C CO2, δ 2 H CH4 and noble gas concentration and isotopes) monitoring program at a small-scale CO 2 injection facility located near Brooks, Alberta, Canada with injection ∼300 m below ground. The results provide a comprehensive record of the subsurface hydrological and geochemical conditions over the six-year period. Injected CO 2 was not detected in samples from the injection zone. There was also no indication of injected CO 2 in samples collected from surface casing vents of the three ∼300 m deep wells, nor was injected CO 2 observed in samples from the six shallow groundwater wells (<105 m deep). Various compositional and isotopic changes have been observed over time which are interpreted to either be indirectly related to CO 2 injection or completely unrelated indicating non-CO 2 injection related variability in the baseline conditions of the site. Additionally, a progressive reduction in hydraulic head has been observed in some shallow aquifers consistent with drought conditions in the region. Our study implies that complex subsurface changes may occur at CO 2 storage sites which may be unrelated to human activity, complicating the monitoring of CO 2 injection.
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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 | 0.000 |
| 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".