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Record W4404014400 · doi:10.2118/222346-ms

Novel Multifunctional Chemical Approaches for Extending Electro Submersible Pumps Run Life and Clearing Solid Build-Up

2024· article· en· W4404014400 on OpenAlexaff
Rosanel Morales, Alexander Davis

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsConocoPhillips (Canada)
Fundersnot available
KeywordsClearingComputer scienceProcess engineeringBiochemical engineeringEngineeringMarine engineering

Abstract

fetched live from OpenAlex

Abstract The impact that organic solids deposition, such as paraffin, asphaltene, sand and scale create on key components of an Electric Submersible Pump (ESP) in oil fields is paramount. Obstruction at the intake and stages of the ESP reduces flow and increases head losses. The presence of these conditions during the ESP operation can increase the likelihood of premature failures related to the mechanical components, such as shaft and the pump stages, affecting performance. This can also accelerate or affect the electrical integrity of components such as pot head, cable, and motors, which are often affected by these solid depositions. Conventional methods to remove this induced damage, like solvents and traditional surfactant and/or conventional acid formulations, can be inefficient and struggle to break and remove damage. This might involve adjusting chemical treatments based on prevalent deposits or modifying ESP design to handle higher particulate levels. Implementing a comprehensive deposit management strategy is vital for maintaining ESP functionality and extending operational life. Combining preventive measures, regular well surveillance, and responsive remediation techniques can protect investments and ensure continuous, efficient production. These advancements in chemical treatments and ESP technology will enhance operators’ ability to manage these challenges effectively. This study investigates the use of multifunctional chemical technologies to replace traditional methodologies (solvents and thermal treatments) used to address deposit buildup and minimize environmental and downhole equipment performance impacts. Exploring the effectiveness of this technology, which can be delivered mixed in water or hydrochloric acid, aims to enhance operational efficiency, and reduce costs associated with downhole equipment maintenance. This approach assesses the ability of these methods to remove paraffin and other depositions with a single effective stage job without damaging the internal ESP system and minimizing soaking time. These results highlight the potential of multifunctional technology in treating ESP, offering a practical and sustainable alternative for maintaining system integrity in severe deposition environments. Laboratory testing and field trial results have been analyzed based on organic and inorganic damage removal efficiency, and their compatibility with elastomers and mechanical components commonly used in the oil industry. Trial results demonstrated an increase in the pump running life of 232%, reduction in the drawdown of 20% with nearly 100% runtime (not obtained before), and additional cost savings of ~$150K. This new approach demonstrated the potential of the technology as a safe and effective alternative for cleaning wells using different Artificial Lift Systems, such as ESP, maintaining elastomer integrity and reducing associated risks. This paper's work studies the effect of multifunctional chemistry when used to remove solid deposits inside artificial lift system units, and presents testing, application, and field results across the Permian Basin. The potential of this technology illustrates exceptional performance in critical operational environments, providing a nonaggressive solution to ESP components compared to traditional solvents.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.647
Threshold uncertainty score0.519

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.033
GPT teacher head0.244
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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