Viscosity Reduction and Carrying Characteristics of a New Downhole Mixer in Heavy Oil Recovery
Bibliographic record
Abstract
Downhole dilution of heavy oil is an effective method for efficient exploitation of heavy oil resources.For this purpose,a new downhole mixer was designed by combining swirl generation technique and Laval nozzle principle.Numerical simulation was made to clarify the variation of viscosity reduction and carrying characteristics of this new mixer with various operating parameters.The study results show that the design concept of axial swirl and tangential opening induced reverse swirl can mix heavy oil and light oil effectively to reduce the viscosity of heavy oil and thus stimulate the heavy oil recovery.The viscosity reduction and heavy oil lifting and carrying effects of this new mixer are influenced by the pressure difference between heavy oil inlet and main outlet as well as that between light oil inlet and heavy oil inlet.Reducing the main outlet pressure and increasing the light oil inlet pressure enable to reduce the mixing viscosity and increase the dilution ratio and viscosity reduction ratio.The working conditions should be set reasonably based on the demands of production and transportation,so as to reduce the consumption of light oil,increase the heavy oil production and reduce the transportation viscosity simultaneously.The conclusions can provide a theoretical reference for improving heavy oil recovery.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".