Power consumption evaluation for electrical submersible pump systems
Bibliographic record
Abstract
Due to cost increase in the current energy market, the requirement for power consumption evaluation and improvement for electrical submersible pump (ESP) systems remains strong. However, there are no developed standards for such evaluation, which makes it a difficult task for the oil industry. This paper intends to introduce suitable approaches and general criteria for the power consumption evaluation and improvement purpose. A comprehensive study and research is performed using two methods to evaluate power consumption for ESP systems. Method 1 is to determine power consumption using the measured KW-hours during a specific period divided by the production rate in barrels per day and by lifted fluid in feet. Method 2 is to calculate overall pumping system efficiency. The status of the two existing methods is that Method 1 is developed with some rule of thumb criteria, while Method 2 unfortunately only consists of a set of calculation formula but no criterion available. Relationship between the two methods is analyzed. General criterion for power consumption evaluation and improvement for ESP wells are proposed in the paper. A case study is provided to clearly demonstrate the application of the criterion.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 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".