Novel Organobimetallic Liquid Catalyst for Enhancing Oil Recovery in Sand-Pack Columns
Bibliographic record
Abstract
Abstract The employing of a self-synthesized organobimetallic catalyst as a viscosity reducing agent to upgrade the heavy oil as well as the mechanisms of enhancing heavy oil recovery are investigated in this study. The components in treated and untreated heavy oil (saturates, aromatics, resins, and asphaltenes or SARA) were assessed, as well as the effects of organobimetallic liquid catalyst (OLC) on viscosity, density, and interfacial tension (IFT) of heavy oil samples were investigated. The results indicate that the OLC-treated heavy oil exhibited reduced viscosity and density. The findings also demonstrate that the presence of the OLC significantly altered the heavy oil's composition and eliminated several contaminants. The effects of OLC treatment on heavy oil recovery were also studied. OLC enhanced the mobility of heavy oil by reducing the IFT of oil brine and increased the recovery factor by 20.36% when compared to untreated heavy oil. These findings will need to be further refined and tested in terms of OLC concentration and other process parameters, but they shed light on a promising initial step toward commercial applications.
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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".