Downhole Heavy Crude Oil Upgrading Using CAPRI: Effect of Steam upon Upgrading and Coke Formation
Bibliographic record
Abstract
Heavy crude oil and bitumen are characterized by a low yield of light distillates in the range of 10–30% with a boiling point below 350 °C, high density (low API gravity), high viscosity, and high heteroatom content, which impede their exploitation. In this study, the catalytic upgrading process in situ (developed by the Petroleum Recovery Institute, Canada) add-on to the toe-to-heel air injection for the extraction and upgrading of heavy oil and bitumen downhole was investigated. The effect of steam addition and steam-to-oil ratio upon upgrading, coke formation, sulfur and metal removal were examined using a Co–Mo/γAl 2 O 3 catalyst at a reaction temperature of 425 °C, pressure of 20 bar, gas-to-oil ratio of 500 mL·mL –1, and steam-to-oil ratio in the range of 0.02–0.1 mL·mL –1 . It was observed that the coke content of the spent catalyst reduced from 17.02 to 11.3 wt % as the steam-to-oil ratio increased from 0.02 to 0.1 mL·mL –1 compared to 27.53 wt % obtained with only nitrogen atmosphere after 15 h time-on-stream. Over the same range of conditions, 88–92% viscosity reduction was obtained as steam-to-oil ratio increased compared to 85.5% in nitrogen atmosphere only, a substantial reduction from the value of 1.091 Pa·s for the feed oil. It was also found that although desulfurization increased from 3.4% in a steam-free atmosphere to 16–25.6% over the increasing range of steam flows investigated, demetallization increased from 16.8% in a steam-free environment to 43–70.5% depending on the increasing steam-to-oil ratio.
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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".