Studies on the Chemical Stability of Glutaraldehyde in Produced Water
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Description Glutaraldehyde is one of the few biocidal actives approved for use in North Sea operations, and has long been used to protect crude oil pipelines from microbial fouling. However, glutaraldehyde degradation has been observed in produced water (PW). In an effort to understand and control this degradation, stability tests were performed in the laboratory. Specific factors which accelerate degradation were identified. Strategies for dosing glutaraldehyde optimally to maintain microbial control in PW will be discussed. Application This study is applicable to microbial control and asset integrity in produced water applications. We aim to develop a better understanding of how glutaraldehyde behaves in complex systems so dosing guidelines can be made more robust and customized to specific situations. Results, Observations, and Conclusions Analysis of glutaraldehyde stability was performed in field and synthetic PW samples. The degradation profile was similar in both water types, indicating a good match between the field and synthetic samples. The most significant factors in glutaraldehyde degradation were temperature and the presence of ammonium chloride. Other factors were also significant, as indicated by the fact that glutaraldehyde in synthetic seawater containing ammonium chloride degrades far slower than in PW at the same temperature and ammonium chloride concentration. Additionally, lower starting concentrations of glutaraldehyde degraded to a greater extent than higher concentrations. This suggests that batch dosing will be more effective than continuous low-concentration doses. Significance Protection of assets and hydrocarbons from microbial contamination and fouling is a major concern in the oilfield. While effective chemicals for microbial control are readily available, their use is often limited by regulatory, environmental, and compatibility concerns. It is therefore very important to understand the chemistry of the available products in a given system such that the most appropriate treatment can be chosen and applied to maintain adequate microbial control.
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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 it