High efficiency and adaptability of mini-hydrocyclones for oil–water separation
Bibliographic record
Abstract
The use of mini-hydrocyclones for downhole oil–water separation has been proposed due to their small size, convenient arrangement, simple structure, and high separation efficiency, all of which contribute to an improved economic recovery rate in oil fields. Currently, mini-hydrocyclones are primarily used for solid–liquid separation, and the flow field characteristics and mechanisms for improving the separation efficiency of mini-hydrocyclones in liquid–liquid separation are not fully understood. This paper elucidates the mechanism of high efficiency in oil–water separation mini-cyclones from a flow field perspective by combining numerical simulations with high-speed photography. The focus is on investigating the flow field characteristics of mini-cyclones with different diameters, including velocity fields, pressure fields, and oil nuclei morphology. The results show that under an oil volume fraction of 2%, the Euler numbers of mini-hydrocyclones with diameters of 30, 24, and 18 mm are 0.23, 0.25, and 0.34 times those of the 12 mm mini-hydrocyclone, respectively, while the Reynolds numbers are 4.20, 3.60, and 2.29 times those of the 12 mm mini-hydrocyclone. This suggests that a smaller mini-hydrocyclone diameter leads to higher energy consumption, weaker turbulence, and better separation efficiency. Under identical operating conditions, a smaller mini-hydrocyclone diameter results in lower tangential and axial velocities, which increases the residence time of fine oil droplets within the device, thereby improving the separation effect. Additionally, an adaptability study of mini-hydrocyclones with different diameters under the same separation ratios and inlet flow conditions was conducted using both numerical simulations and laboratory experiments. The findings reveal that, under the same operating conditions, the smaller the diameter of the mini-hydrocyclones, the higher their efficiency. Under the optimal operating conditions within the scope of the study, the separation efficiencies of the 12 and 24 mm mini-hydrocyclones were 99.8% and 98.5%, respectively. Additionally, the experimental and simulated data for separation efficiency and underflow oil concentration demonstrate a second-order fitting result greater than 0.92, indicating a high degree of consistency.
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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".