Use of Nitrate or Nitrite for the Management of the Sulfur Cycle in Oil and Gas Fields
Bibliographic record
Abstract
Abstract The production of sulfide by sulfate-reducing bacteria (SRB) in oil and gas fields causes problems including enhanced corrosion risk, reservoir plugging and deterioration of product quality. Injection of nitrate or nitrite stimulates heterotrophic nitrate-reducing bacteria (hNRB), which compete with SRB for oil organics, such as volatile fatty acids (VFA). Nitrate also stimulates nitrate-reducing, sulfide-oxidizing bacteria (NR-SOB), which lower sulfide levels. Nitrite is a strong and specific inhibitor of the SRB enzyme responsible for sulfide production, whereas nitrate does not inhibit SRB. Hence, injection of nitrate or nitrite can prevent or remediate problems in the oil and gas industry caused by SRB activity, provided hNRB and NR-SOB are present. A survey of 8 oil fields, 2 gas storage reservoirs and an oil storage tank indicated that SRB and hNRB were widely distributed, whereas the distribution of NR-SOB appeared more limited. The SRB and hNRB were able to use lactate, as well as VFA as electron donor for sulfate or nitrate reduction. However, the order of use of VFA components appeared to differ with acetate being used preferentially by hNRB and propionate and butyrate being used preferentially by SRB. The production of nitrite by hNRB and NR-SOB varied greatly with quantitative conversion of nitrate to nitrite (up to 30 mM) being observed in one case; the nitrite formed was then reduced further. Samples from a high temperature North Sea oil field had thermophilic SRB, but no hNRB or NR-SOB activity, causing sulfide production to be inhibited by nitrite only. Although nitrite appeared to react chemically with sulfide under these conditions, causing all nitrite to disappear within 100 h, the observed inhibition was long-lasting (>500-1500 h). Hence, nitrite can be used successfully to control SRB activity in fields where hNRB and NR-SOB are absent. In summary, it appears that many oil and gas fields contain hNRB and NR-SOB populations, which are activated upon injection of nitrate or nitrite, allowing sulfide remediation in situ. Characterization of these populations as described in this paper may allow prediction whether these injections will be successful and whether use of nitrate or of nitrite is preferred.
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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) | 0.000 | 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 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".