Trials of VSD Electrical Signature Analysis Technology for ESP Vibration in High Dog Leg Severity Wells at Surmont
Bibliographic record
Abstract
Abstract ESPs operating in high dog leg severity (DLS) wells are prone to bending loads and vibration levels that may contribute to early failure modes such as shorted motor stators, rotor strikes and shaft breaks. Electrical signature analysis (ESA) has recently shown potential to identify the operating state of an ESP by analyzing high frequency data (current and voltage) captured at the variable speed drive (VSD). This paper shows how ESA helped identify the vibration under bending state on three ESPs installed sequentially in a well where the two previous ESP installs had failed prematurely. The premature failures occurred at a high DLS pump setting depth due to rotor strikes under bending. ESA contributed to an enhanced understanding of the operating conditions of ESPs and, in conjunction with other changes (such as ESP length, pump setting depth and operating frequency), helped to significantly extend the runtime of ESPs in this challenging well.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".