Compositional Effect on the Low-Temperature Oxidation of Crude Oils Subjected to In Situ Combustion
Bibliographic record
Abstract
This work shows the compositional effect on low-temperature oxidation of crude oils subjected to in situ combustion (ISC). Three heavy crudes were used in this study in which detailed information on the molecular species involved in ISC was obtained by ultra-high-resolution mass spectrometry. The oxidation was carried out on a mixture of 2% of crude oil in Ottawa sand in an isothermal cell using a batch system at 1500 psi at three conditions: (i) reservoir temperature of each crude oil, (ii) 180 °C, and (iii) 180 °C using a heterogeneous catalyst-type β-MnO 2 . The oil remaining after the reaction was extracted from the sand and characterized by FT-ICR MS using (+) atmospheric pressure photoionization and (−) electrospray ionization modes. The acidity of the oxidation products (extracts) and the composition of the produced carbon oxides were also monitored. A greater amount of carbon oxides produced, a lower extraction yield of organic matter in the sand after the reaction, and a higher acidity in the extracts, implied a higher reactivity. In the same sense, a higher reactivity was observed for the sample with the highest sulfur content and over the most aromatic compounds. The use of the catalyst at 180 °C promoted the oxidative reactions in two of three of the oils, as well as the formation of polyoxygenated acids over monocarboxylic acids for one of the oils, which implies that the application of this technology strongly depends on the composition of the oil.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".