Impact of salinity on coagulation and dissolved air flotation treatment for oil and gas produced water
Bibliographic record
Abstract
Produced water is a major wastewater stream in the oil and gas industry which typically consists of dispersed and dissolved oils, and high levels of salinity. Despite concerns that dissolved aromatics in produced water may be detrimental to marine life, discharge regulations and treatment technologies for produced water largely focus on dispersed oil and grease removal. The purpose of this research project was to investigate coagulation with ferric chloride (FeCl3) and dissolved air flotation (DAF) at bench-scale for the removal of both dispersed and dissolved oils from synthetic and offshore produced water samples, with a specific focus on the impact of salinity on the coagulation process. Coagulation and DAF treatment of the produced water samples achieved high removals of dispersed oil and grease, but had limited impact on dissolved aromatics. The coagulation process in the saline produced water samples reduced dispersed oil and grease concentrations from 100 mg/L to below North American discharge limits (i.e. 30 mg/L in Canada, 29 mg/L in the USA) under all conditions tested, while the effectiveness of coagulation treatment in the fresh water synthetic samples was highly dependent on coagulation pH.
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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 | 0.001 |
| 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 | 0.001 | 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".