The Catalytic Effect of Clay on In-Situ Combustion Performance
Bibliographic record
Abstract
Abstract The in-situ combustion (ISC) is highly effective thermal enhanced oil recovery process in which high displacement efficiencies can be accomplished. While several physical and chemical factors affect the ISC performance, there is a little knowledge about how each parameter changes the ISC fate. In this study, we investigate the catalytic effect of clay on different crude oil types. Six one-dimensional combustion tube experiments were conducted on three different crude oil samples; one from Mexico and two from Alberta, Canada. The combustion behavior of each crude oil sample was tested with two combustion runs; by preparing reservoir rock with only sand (E1, E3, and E5) and by preparing reservoir rock with 3 wt% clay and 97 wt% sand mixture (E2, E4, E6). The combustion characteristics were monitored with temperature profiles, produced gas compositions, and produced liquid yields. The level of in-situ oil upgrading were determined by comparing the viscosities of produced oil samples with the original ones. The results showed that the catalytic effect of the clay controls the combustion front propagation, the fuel formation, and the produced oil quality. Clays visualized on postmortem samples in the shape of lumps indicate that clay alteration occured at elevated temperature due to interaction of clay with crude oil and due to thermal decomposition of clay. It was observed that the lump formation was associated with mainly saturates and asphaltene contents of initial oil and asphaltene-clay interaction during fuel formation. Our results support that the clay presence in reservoir rock had an impact on ISC performance. However, this impact did not have a linear trend and the response of the catalytic effect of clays were different from one crude oil to another; while one crude oil favored combustion more with the presence of clay, the other did not and led to lower oil production by producing more gas.
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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".