Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The role of foamy oil flow in cold production of heavy oil has attracted considerable attention in the literature. It has been suggested in several studies that there may be a link between the presence of high Asphaltenes content and the foamability of oil. However, a systematic examination of the impact of Asphaltenes on the performance of solution gas drive, in connection with foamy oil flow, has not been reported. This paper presents an experimental study that addresses this issue. The objective of this study was to examine whether or not the presence of Asphaltenes has a strong influence on the performance of foamy solution gas drive. To this end, parallel solution gas drive experiments were conducted with a heavy crude oil from Lloydminster area and a de-asphalted version of the same oil. To eliminate the influence of oil viscosity, the original crude oil was diluted with a 50-50 mixture of heptanes and toluene to reduce viscosity to the same level as that of the de-asphalted oil. The experiments were carried out in a visual sand pack that permited observation of bubble formation in the sand. The results show that the effect of asphaltene content varies with the depletion rate. At higher depletion rates, the oil recovery and production profile of crude oil with asphaltene is different from those without asphaltenes. The presence of asphaltenes, appears to facilitate bubble nucleation, decreases the critical super-saturation and helps in maintaining the dispersed gas flow by suppressing bubble coalescence. However, as the depletion rate declines, the incremental recovery due to asphaltenes diminishes. The two crude oil samples provided similar recovery and production profile when the depletion rate was the slowest one used in this work.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it