Minimising hydrogen sulphide generation during steam assisted production of heavy oil
Bibliographic record
Abstract
The majority of global petroleum is in the form of highly viscous heavy oil. Traditionally heavy oil in sands at shallow depths is accessed by large scale mining activities. Recently steam has been used to allow heavy oil extraction with greatly reduced surface disturbance. However, in situ thermal recovery processes can generate hydrogen sulphide, high levels of which are toxic to humans and corrosive to equipment. Avoiding hydrogen sulphide production is the best possible mitigation strategy. Here we use laboratory aquathermolysis to reproduce conditions that may be experienced during thermal extraction. The results indicate that hydrogen sulphide generation occurs within a specific temperature and pressure window and corresponds to chemical and physical changes in the oil. Asphaltenes are identified as the major source of sulphur. Our findings reveal that for high sulphur heavy oils, the generation of hydrogen sulphide during steam assisted thermal recovery is minimal if temperature and pressure are maintained within specific criteria. This strict pressure and temperature dependence of hydrogen sulphide release can allow access to the world's most voluminous oil deposits without generating excessive amounts of this unwanted gas product.
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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".