Insights Into Bitumen Viscosity Reduction Using Ultrasound-Assisted EOR
Bibliographic record
Abstract
Abstract The present work clarifies the mechanisms associated with bitumen viscosity reduction during ultrasound sonication. A Canadian (CDN) and Nigerian (NGR) bitumen, selected for this study, have a respective viscosity of 2,617 and 12,043 cP at room temperature. Two series of ultrasound sonication experiments were performed using an ultrasonic generator and the submersible traducer. A series of experiments at 28, 38 and 200 kHz under ambient (air)-environment revealed that sonicating the oil continuously for 3 h at 200 kHz reduced NGR viscosity from 12,043 to 2,079 cP and the asphaltene content from 3.21 to 1.14 wt.%. Under the same conditions, CDN viscosity reduced from 2,617 to 486 cP and its asphaltene content increased from 5.72 to 8.11 wt.%. A reverse trend was observed at 38 kHz. For an average of 70% viscosity reduction, asphaltene content increases to 7.94 wt.% for NGR and decreases to 1.03 wt.% for CDN. On the other hand, bitumen sonication at 38 kHz under nitrogen (N2), and carbon dioxide (CO2) environment showed that irradiating NGR for 3 h under an N2 environment resulted in the lowest oil viscosity of 3,274 cP. However, the asphaltene content increases to 16.3 wt.%. Changing the gas environment to CO2 and air could reduce the viscosity to 4,415 and 9,773 cP, respectively. The asphaltene content decreases to 15.1 and 2.37 wt.%, concurrently. No direct relation between asphaltene content and viscosity reduction was established. Nevertheless, the viscosity reduction is influenced either by the applied frequency or gas environment. The minimum energy required to initiate the flow increased with the applied frequency and was fairly altered by the change in the gas environment.
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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 | 0.001 |
| 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".