Some Compositional Viscosity Correlations for Crude Oils from Russia and Norway
Bibliographic record
Abstract
The current work is based on experimental viscosity and compositional data of about 200 crude oil samples from various parts of Russia and the Norwegian continental shelf. Data analyses were performed to estimate correlations between viscosity and density values as well as concentrations of main components from the crude oils of different origins. It appeared that, in some cases, it is possible to establish a general correlation of viscosity increase along with growing asphaltene, resin, and aromatics contents but also a decrease in viscosity with increasing saturates content. The spread of the data points can be rather wide for the oils of different origins. It was observed that asphaltenes from all of the crude oil samples acted as promoters of the viscosity growth at rather low concentrations, while resins and aromatics effectively increased viscosity in a higher concentration range. The effect of asphaltenes on the viscosity of real crude oils seems to be more important than when dissolved in a model solvent (xylene). This means that either the asphaltenes have a different solvation state in crude oils compared to xylene or asphaltenes are not solely responsible for the high viscosity of the crude oils.
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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".