Recent Experience from Field Application and Laboratory Testing on the Corrosion Risk of Stainless Steel UNS S82551 in Water Alternating Gas Service
Bibliographic record
Abstract
Abstract Duplex stainless steel UNS1 S82551 tubing has been used since 2017 in Water Alternating Gas (WAG) injection wells on the Norwegian continental shelf. After approximately five years of operation, leaks were reported in two wells. Investigations were performed to determine the root cause of these failures, including a review of the metallurgy and fluids used during well construction and operation phases. The metallurgy included, amongst others, the following alloys: UNS S82551, UNS S39274 and UNS N09925. Inspection of the retrieved well components revealed that the leaks were caused by crevice corrosion to the tubing threaded connections. UNS S82551 is expected to be corrosion resistant in WAG service utilizing treated seawater and dried gas. However, earlier extensive laboratory testing showed that this alloy can be sensitive to crevice corrosion under seawater treatment deviations. Subsequent laboratory corrosion testing including all fluids in contact with the well materials during construction showed no impact on crevice corrosion. The root cause analysis revealed that the operating treatment procedure allowed residual chlorine in the injected seawater. Immersion and electrochemical testing confirmed that the conditions of exposure induced by the operation procedure led to crevice corrosion of alloy UNS S82551, and this was the root cause of the tubing leaks.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".