Quantitative Laboratory Assessment Of Aquathermolysis Chemistry During Steam-assisted Recovery Of Heavy Oils And Bitumen, With A Focus On Sulfur
Bibliographic record
Abstract
Abstract The production of gaseous sulfur-containing species during the steam-assisted recovery of heavy oil and bitumen presents problems owing to their toxicity, corrosion properties and odor. In order to quantitatively study aquathermolysis sulfur chemistry during the thermal (steam-assisted) recovery of heavy oils we have subjected a well-characterized and sulfur-rich bitumen core sample to 150 - 325°C and 70 - 1740 psia (0.48 - 12 MPa) conditions in the continued presence of liquid water for 24 hours. The reaction products include gases, oil flotate, oil sinkate, water-soluble products, and water- insoluble residues. All have been studied with a variety of analytical techniques, including FTIR spectroscopy, chromatographic fractionation (SARA analysis), GC-FPD and GC-MS. Moreover, these techniques have been extended to analysis of the asphaltene fractions. Results suggest that some in-situ upgrading of the oil occurs under these conditions; additionally, gaseous hydrogen sulfide is released at temperatures at and above 250 °C. Variations in the relative abundances of solubility classes and chemical fractions imply that the source of sulfur is via the thermal degradation of resins and/or asphaltenes. The experimental methods, results and quantification approach discussed herein will be useful to support the development of models for engineering design of facilities for the steam-assisted recovery of heavy oils and bitumen.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".