Control of SRB – Mediated Microbially Influenced Corrosion in Flowing Systems
Bibliographic record
Abstract
Corrosion is the major threat to oil and gas production and transportation infrastructure around the world. It is now accepted that microorganisms, especially sulfate-reducing bacteria, may play a significant role in the corrosion mechanism in many of the corrosion scenarios in the oil and gas industry. Therefore, an understanding of how to control sulfate-reducing bacteria mediated microbially influenced corrosion is key to controlling microbially influenced corrosion in the oil and gas industry. The biocorrosion threat to a steam-assisted gravity drainage operation was assessed and found to be low. The control of sulfate-reducing bacteria mediated microbially influenced corrosion in model systems involving carbon steel beads under flow was accomplished with biocides and corrosion inhibitors. While significant corrosion control was observed with biocides, oil soluble corrosion inhibitors reduced the corrosion rate by as much ninety-nine percent. These control methods had different effects on the microbial communities involved in the corrosion process.
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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) | 0.001 | 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".