The Corrosiveness of Nitrite in a Produced Water System
Bibliographic record
Abstract
Abstract Increasing concentrations of sodium nitrite were added to synthetic North Sea produced water in the presence of either 1 bar CO2 or N2 to determine its effect on corrosion. These tests were run at 80°C in the presence of sulfide and at a sheer stress up to 25 Pa. The test materials were either A106 carbon steel or duplex stainless steel, representing the range of materials typical of upstream production equipment. Nitrite is an effective inhibitor of sulfate reducing bacteria activity as well as an enhancing agent for biocides. Because it is a green chemical it is desirable for controlling Microbiologically Influenced Corrosion (MIC) in oilfield brines. Although known to be an effective anodic corrosion inhibitor in fresh water systems its inhibitory effects in oilfield brines are less understood. Duplex stainless steel did not show any enhanced corrosion in an inert or CO2 environment in presence of nitrite. In the case of carbon steel, nitrite displayed an inhibiting role when exposed to 1 bar CO2 at 80°C. Increases of chlorides or sulfates had only a small effect on increasing corrosion rates in the presence of nitrite and CO2. However, in the presence of an inert gas, increases in nitrite above 2 mM significantly increased corrosion rates of carbon steel. The addition of small amounts of sulfide in the presence of 2 mM nitrite resulted in a small increase in corrosion rates of carbon steel as did the impact of 25 Pa of sheer stress. The presence of 2 mM nitrite interfered with the corrosion inhibiting activity of a commercial inhibitor in the presence of CO2. This paper presents results of testing performed to determine the corrosiveness of nitrite in synthetic North Sea produced water.
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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".