Bitumen and Heavy Oil Rheological Properties: Reconciliation with Viscosity Measurements
Bibliographic record
Abstract
Complex viscosity and phase-angle measurements for Athabasca bitumen and Maya crude oil were performed with a rotational rheometer using parallel plates and a double gap cylinder in the oscillatory mode over the temperature range of (200 to 410) K. A large range of shearing conditions were applied (frequency of oscillations, shear strain, or stress), and up to three orders of magnitude of variations in measured viscosity values for individual samples at a fixed temperature were obtained. Athabasca bitumen and Maya crude oil were found to be solid-like materials up to (260 to 280) K and (230 to 240) K, respectively. Athabasca bitumen is a non-Newtonian shear-thinning fluid up to (310 to 315) K, whereas Maya crude is a shear-thinning fluid up to (280 to 285) K. Both are Newtonian at higher temperatures. Maya crude oil was also found to possess thixotropic behavior. Athabasca bitumen reveals the thermal irreversibility of complex viscosity, if it is heated above 360 K. These rheological behaviors are attributed to the multiphase behavior of these materials over the temperature range of interest, and these results can be used to reconcile the large differences in reported viscosity values for bitumen and heavy oil obtained with diverse viscometers where shear rate and other variables are not controlled. Additional artifacts introduced during measurements are also addressed. Sample variation due to geographical location, depth of formation, and production and postproduction processing can also result in up to three orders of magnitude of differences between the measured “viscosity” of bitumen when the measurement method and temperature are fixed. The flow properties of bitumen and heavy oil are expected to be strong functions of sample source and the hydrodynamics prevailing in situ or in processes at temperatures where non-Newtonian behaviors prevail.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".