Tracking leakage from a natural CO<sub>2</sub> reservoir (Montmiral, France) through the chemistry and isotope signatures of shallow groundwater
Bibliographic record
Abstract
Abstract Natural accumulations and releases of CO2 provide the opportunity to study the CO2 trapping and migration mechanisms, the potential impacts of CO2 leaks, and the monitoring tools to assess the impacts of geological storage of anthropogenic CO2. Previous studies on the deep CO2 reservoir of Montmiral (France), focusing on soil gases, groundwater, as well as deep fluids, did not detect any signs of leaks and despite high CO2 fluxes suspiciously high δ13C values have not been stated. In order to further investigate whether some CO2 has leaked from the reservoir toward the surface, we focus here on the major and trace element geochemistry of the shallow aquifers overlying the reservoir with a special focus on the carbonate system, using isotope tracers potentially sensitive to leaks (δ13C of DIC, 87Sr/86Sr and stable isotopes of water). A forward modeling of the potential evolution of groundwater in case of leaks was performed, combining equilibrium calculations of the carbonate system and an ad hoc carbon isotope model. Most observed δ13C values are compatible with modeled carbonate dissolution under open or closed conditions with respect to CO2. A 13C‐enriched subset of samples shows clear signs of incongruent dissolution of Mg‐Sr‐calcite or dolomite, corroborated by 87Sr/86Sr ratios, so that mixing with isotopically heavy deep CO2 is not required to explain the observed chemical and isotope data. The absence of any sign of CO2 leakage into shallow groundwater would support the fact that the reservoir and caprock have been trapping the CO2 efficiently over millions of years.
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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 | 0.000 | 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 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".