Field-scale time-domain spectral induced polarization monitoring of geochemical changes induced by injected CO2 in a shallow aquifer
Bibliographic record
Abstract
ABSTRACT Contamination of potable groundwater by leaking CO2 is a potential risk of carbon sequestration. With the help of a field experiment, we investigated whether surface monitoring of direct current (DC) electric resistivity and induced polarization (IP) could detect geochemical changes induced by CO2 in a shallow aquifer. For this purpose, we injected CO2 at depths of 5 and 10 m and monitored its migration using 320 electrodes on a 126 × 25 m surface grid. Measured resistances and IP decay curves found a clear signal associated with the injected CO2 and rebounded to preinjection values after the end of the injection. Full-decay 2D DC-IP inversion was used to invert for the subsurface distribution in Cole-Cole parameters and changes to these parameter fields over time. The time-lapse inversions found plumes of decreased resistivity and increased normalized chargeability. The two plumes were of different shapes, with the resistivity anomaly being larger. Comparison with measurements of electric conductivity and aluminum (Al) concentrations indicated that two geochemical processes were imaged. We interpreted the change in resistivity to be associated with the increase in free ions directly caused by the dissolution of CO2, whereas the change in normalized chargeability was most likely linked to persistent acidification and best indicated by Al concentrations. The results highlight the potential for monitoring of field scale geochemical changes by means of surface DC-IP measurements. Especially the different developments of the DC resistivity and normalized chargeability anomalies and the different associated geochemical processes highlight the added value of IP to resistivity monitoring.
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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".