Theoretical and Experimental Investigation of Isothermal Compositional Grading
Bibliographic record
Abstract
Summary A centrifuge system capable of producing a potential difference across a live oil column equivalent to 1,000 ft of gravitational head was designed and tested. Initial tests on a simple ternary system yielded results similar to equation-of-state (EOS) models. A black-oil sample from a Gulf of Mexico field, Bullwinkle J2-RB sand, exhibiting compositional gradients was segregated in the centrifuge. Experimental results from the centrifuge were similar to field values, indicating that the large variation in composition observed for this field may be attributed to gravitational segregation alone. From the results of these two sets of experiments and the subsequent analysis of the graded fractions, we can conclude that significant compositional variation of reservoir fluids not near their vapor/liquid critical points can be caused by gravity alone. The grading phenomenon is sensitive to the saturate/aromatic balance of the oil. Existing EOS models did not correctly predict the compositional variations in fluids like the Bullwinkle J2-RB because pseudocomponents generated from volatility distributions have a fixed saturate/aromatic character. It is subtle changes in the saturate/aromatic balance that drive the grading phenomena for these fluids.
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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 | 0.001 |
| 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) | 0.002 | 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".