Technical Challenges and Learnings from a High Temperature Metallic Progressing Cavity Pump Test
Bibliographic record
Abstract
Abstract Metal-to-metal Progressing Cavity Pump (M PCP) technology has become an effective lifting method for challenging thermal conditions, such as for Steam Assisted Gravity Drainage (SAGD) production. This paper summarizes some of the technical challenges and key learnings following a unique high temperature test on an M PCP system developed by National Oilwell Varco (NOV), which was conducted in a high temperature flow loop at C-FER Technologies. This M PCP pumping system was evaluated by ConocoPhillips as part of their High Temperature Artificial Lift Validation program, the objective of which has been to test the performance of multiple forms of AL under SAGD-like conditions while at high fluid temperatures of 250°C (482°F). In addition to an evaluation of the M PCP system (i.e. including an assessment of the break-in period, levels of downhole vibration, rod torque, etc.) this program was unique in that it also assessed the performance of the same metallic PCP stator using two different PCP rotors, to mimic a rotor-swapping operation. Some of the challenges encountered during this test program including issues with the downhole completion, high levels of downhole vibration, and significant casing and tag-bar wear. This paper will summarize some of the technical challenges and lessons learned, in addition to sharing some of the key pump performance results for this unique M PCP test program.
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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 | 0.000 |
| 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".