Bibliographic record
Abstract
Abstract Due to some particular advantages, such as the maximum suitable artificial lift system for heavy and sandy wells, higher pump efficiency and power saving, PCP (Progressive Cavity Pump) is becoming one of the popular oil artificial lift system in recent years. PCP artificial lift technology is up to 12% all over the world averagely, and 50% in Canada. For normal heavy oil (viscosity ≤1000CPo), the oil can be lifted to the surface only using conventional PCP system. But for the more viscosity oil (viscosity ≥1000CPo), the viscosity and frictional resistance in the formation and annular (between tube and sucker rod) will induce a very big difficulty for the oil flowing from the formation to pump depth and from pump depth to the surface, so some assistant measures must be used with PCP system to lift the oil from downhole to surface. For SAGD (Steam Assisted Gravity Drainage), CSS (Cyclic Steam Stimulation) and SFD (Steam Flooding Drive) wells, steamed gas is assisted to decrease the oil viscosity to enhance its fluidity. PCM Vulcain™ (PCP with metal stator and metal rotor) had been successfully applied in such kind of wells since 2007. And PCM PCP with 198 high temperature resistant elastomer had been successfully used in 4 CSS wells. In addition, several high viscosity wells are producing with normal PCM PCPs assisted with light oil mixing system, hot water injecting system and electricity heating system. This paper will discuss the successful PCP artificial lift system applications with above 5 special assistant systems. This paper will be a guider for such kinds of special PCP technologies to be spread and applied widely in the world.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".