Monitoring carbon dioxide storage using passive seismic techniques
Bibliographic record
Abstract
Carbon dioxide stored in geological reservoirs to reduce anthropogenic emissions must be monitored to ensure that no leakage is occurring. One leakage risk is that injection-induced pressure increases may generate fractures in the caprock, providing a pathway for buoyant carbon dioxide to penetrate the reservoir seal. Geophones can be deployed to detect fracturing events. The rates and magnitudes of seismicity, and their hypocentres, can be used to characterise geomechanical deformation induced by injection, and thereby assess the risks of leakage through fractures. In this paper synthetically modelled data are used to show how surveys should be designed to maximise the potential for this technique within the specific remits of carbon dioxide capture and geological storage (CCS), before discussing several case examples where passive seismic monitoring has been used to monitor subsurface injection of carbon dioxide. Recommendations and suggestions are given for the deployment of passive seismic monitoring as CCS moves from pilot to full-scale demonstration and commercial projects.
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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 | 0.000 | 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) | 0.001 | 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".