CO2 Storage Contingencies Initiative: Detection, Intervention and Remediation of Unexpected CO2 Migration
Bibliographic record
Abstract
High profile refinery, pipeline and well incidents over the past several years may have impacted stakeholder perception of the oil and gas industry's ability to prevent and control accidents. This perception may be translated to current and future CO2 storage projects, as this relatively new application has a limited track record at scale. To better understand unexpected fluid migration and responses, the CO2 Capture Project Phase 3 (CCP3) has developed the "CO2 Storage Contingencies" project. The project was initiated by a CCP3-sponsored workshop that brought together industry, national laboratory and academic experts in wells, reservoir engineering and geosciences. The goal was to systematically assess CO2 and displaced fluid migration scenarios with current versus needed capabilities for detection, intervention and remediation of damages. Three focus areas were addressed in detail: wells, conformance and seals/fractures. It was concluded that groundwater and vadose zone remediation strategies would be deferred owing to decades of related experience and that a focus on intervention might obviate their need. The underlying assumption of the workshop was that even if CO2 storage projects employ state-of-the-art site characterization, risk assessment, and monitoring systems, unexpected migration may nevertheless occur, particularly during the early stages of gaining experience with large scale deployment. Specific mechanisms for unanticipated CO2 and brine migration were identified with both established and novel mitigation approaches for remedying them proposed. The group concurred on a general approach to qualifying scenarios with potential mitigations. A forward plan was outlined to document relevant industry experience with a roadmap of needed research and development (R&D), including modelling, simulation, bench-scale experiments and field trial design through deployment. The initial phases of the study are ongoing with concurrent concept development of the latter phases entailing identification, assessment and possible deployment of a field trial of detection and intervention approaches.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.001 | 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 teacher head, 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".