Laboratory Evaluation of H2S Bioscavenging in Produced Water at 60°C
Bibliographic record
Abstract
Abstract Nitrate can control biogenic souring by lowering sulfate reducing bacteria (SRB) metabolic activity and shifting the microbial community such that nitrate-reducing bacteria (NRB) out-compete SRB for nutrients. Nitrate was applied in a laboratory study using a 20-cc packed bed upflow reactor to determine kinetic rate of H2S removal. The objectives of the testing were to (1) enrich for nitrate-reducing, sulfide-oxidizing microorganisms derived from produced water and (2) determine the kinetic rate of H2S removal at 60˚C in a synthetic medium with an H2S:nitrate molar ratio of 2, and (3) describe the microbial community involved in nitrate-mediated souring control in this system. Sulfide was measured at the face and at the discharge of the column to determine the sulfide oxidation rate. Residence time in the reactor was varied by changing flow rate but a removal rate of nearly 50% H2S was achieved across the column in one hour residence time. This paper provides a description of the microbial community cultivated at high temperature using 16S rRNA to profile the population dynamics resulting from nitrate treatment. Phospholipid fatty acid analysis was also used for taxonomic evaluation and quantifying physiological changes in the biomass due to nitrate treatment.
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How this classification was reachedexpand
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) | 0.012 | 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 teacher head, 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".