Development and Application of a Scale Inhibitor for Electrical Submersible Pumps Suitable for Very Cold Weather
Bibliographic record
Abstract
Abstract Many oil producers in the Rocky Mountains region, USA, make use of electrical submersible pumps (ESP) to assist the lift of produced fluids. This region of the country is well known for its very harsh winters, with outside temperatures as low as −40 °F (−40 °C). ESP failures resulting in increased lifting costs due to workovers, lost oil, and logistics can be caused by many factors, including reservoir solids eroding the ESP or being trapped within the intake and pump stages, mechanical and electrical problems, and scale deposition. ESPs are particularly sensitive to calcium carbonate scale formation due to the extreme skin temperatures that can develop and often require continuous chemical injection to control this problem. Calcium carbonate scale formation in ESPs is a well known contributor to ESP failures. Large pressure drops combined with high temperatures increase the risk of calcium carbonate deposition even in mildly scaling systems. Scale formation on the motor housing acts as insulation, preventing heat transfer from the motor to the well fluids, causing the motor to be insufficiently cooled. Any scale deposition on the pump impellers can cause an imbalance and vibration, degrading pump performance. Continuous scale inhibitor treatment of ESPs to mitigate calcium carbonate scaling is a common practice. However, the choice of scale inhibitor requires careful consideration due to the high skin temperatures that can develop and can lead to inhibitor decomposition. Effective continuous treatment of ESPs during the winter months in regions where very low temperatures can be expected require product formulations capable of withstanding these harsh conditions without significant changes to their physical properties. This paper presents and discusses, with the aid of laboratory and field data, the development and deployment of a thermally stable scale inhibitor suitable for treatment of ESPs that can also be deployed in very cold climates, along with the monitoring tools used to ensure effective treatment.
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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".