Hydrogen sulfide formation in oil and gas
Bibliographic record
Abstract
Hydrogen sulfide (H2S) can be a significant component of oil and gas upstream production, where H2S can be naturally generated in situ from reservoir biomass and from sulfate-containing minerals through microbial sulfate reduction and (or) thermochemical sulfate reduction. On the other hand, the technologies employed in oil and gas production, especially from unconventional resources, also can contribute to generation or delay of appearance of H2S. Steam-assisted gravity drainage and hydraulic fracturing used in production of oil sands and shale oil/gas, respectively, can potentially convert the sulfur content of the petroleum into H2S or contribute excess amounts of H2S during production. A brief overview of the different classes of chemical reactions involved in the in situ generation and release of H2S is provided in this work. Speciation calculations and reaction mechanisms are presented to explain why thermochemical sulfate reduction progresses at faster rates under low pH. New studies regarding the degradation of a hydraulic fracture fluid additive (sodium dodecly sulfate) are reported for T = 200 °C, p = 17 MPa, and high ionic strengths. The absence of an ionic strength effect on the reaction rate suggests that the rate-limiting step involves the reaction of neutral species, such as elemental sulfur. This is not the case with other thermochemical sulfate reduction studies at T > 300 °C. These two different kinetic regimes complicate the goal of extrapolating laboratory results for field-specific models for H2S production.
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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".