Corrosion and Material Degradation in Geological CO2 Storage: A Critical Review
Bibliographic record
Abstract
At present, carbon capture and storage (CCS) is the only mature and commercialized technology capable of effectively and economically reducing greenhouse gas emissions to achieve a significant and immediate impact on the CO 2 level on Earth. Notably, long-term geological storage of captured CO 2 has emerged as a primary storage method, given its minimal impact on surface ecological environments and high level of safety. The integrity of CO 2 storage wellbores can be compromised by the corrosion of steel casings and degradation of cement in supercritical CO 2 storage environments, potentially leading to the leakage of stored CO 2 from the sites. This critical review endeavors to establish a knowledge foundation for the corrosion and materials degradation associated with geological CO 2 storage through an in-depth examination and analysis of the environments, operation, and the state-of-the-art progress in research pertaining to the topic. This article discusses the physical and chemical properties of CO 2 in its supercritical phase during injection and storage. It then introduces the principle of geological CO 2 storage, considerations in the construction of storage systems, and the unique geo–bio–chemical environment involving aqueous media and microbial communities in CO 2 storage. After a comprehensive analysis of existing knowledge on corrosion in CO 2 storage, including corrosion mechanisms , parametric effects , and corrosion rate measurements, this review identifies technical gaps and puts forward potential avenues for further research in steel corrosion within geological CO 2 storage systems.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".