Progressing Cavity Pump Sizing: Black Magic or Science?
Bibliographic record
Abstract
Abstract Progressing cavity (PC) pumps deployed as an artificial lift method have seen their range of use expand from their heavy oil origins in Canada to a wide variety of different applications around the world. This expansion has been enabled by the development of new products to meet the different volume, lift and downhole fluid environment requirements. However the effect of the fluid environment on the PC pumps‘ stator elastomeric lining dimensions and properties and, in turn their impact on pump performance and life, introduces a critical application design consideration. This consideration is commonly referred to in the industry as pump sizing and encompasses the process of adjusting rotor dimensions to compensate for the impact of the downhole environment on the stator. Pump sizing started as a trial and error approach based on pump functional testing. As the fluid environments began to have an increased impact on the stator elastomer, pump sizing came to be recognized as being important to ensuring pump success. Methods for measuring rotors and stators were improved and calculation and sizing methodologies developed. Pump test bench equipment and processes became more sophisticated and their accuracy and reliability improved. Methods for laboratory testing elastomer samples in well fluids were developed to quantify dimensional and mechanical property changes. The second edition of the ISO 15136-1 International Standard for PC Pump Systems for Artificial Lift¹ provides guidelines for component measurement, pump testing and elastomer compatibility testing but does not address the use of this information for pump sizing. Consequently pump sizing is currently done differently across the industry with limited information being provided to end users. This often results in confusion and poor implementation and can detrimentally affect PC pump performance and runtimes. In extreme cases it has led to the characterization of PC pumps as being unsuitable for a particular application when the problem was primarily with the pump sizing. This paper provides an overview of the historical and current state of the different processes associated with PC pump sizing and shows how the newer processes can be applied in a systematic scientific manner to support the successful application of PC Pumps.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".