MétaCan
Menu
Back to cohort
Record W2888810749 · doi:10.2118/190960-ms

Permanent Magnet Motors/Powder Metallurgy Pump Stages: Increasing Profit Margins, Reserves, and Economic Limits through Efficient ESP Design

2018· article· en· W2888810749 on OpenAlexaboutno aff
Jake Lucas, Craig Donham, T. Wróbel

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPowder metallurgyElectric motorHorsepowerMechanical engineeringElectric powerMaterials scienceAutomotive engineeringProcess engineeringEnvironmental scienceEngineeringMetallurgyPower (physics)

Abstract

fetched live from OpenAlex

Abstract High volume, high water cut wells historically present a challenge in terms of economic production. Due to limitations with other forms of artificial lift, electrical submersible pumps are generally chosen for this type of application. Submersible pumps can move large volumes of fluid from great depths but are generally expensive to operate due to poor efficiencies. As electrical rates increase exponentially, permanent magnet motor (PMM) technology and powder metallurgy stage manufacturing can combat expense with high efficiency. Through replacement of the industry standard asynchronous motor (AM) with the PMM, efficiencies have increased from 84% to 93% (Novomet. Permanent Magnet Motor. 2016). Over 10,000 PMMs operate worldwide. On top of PMMs, high-efficiency powder metallurgy centrifugal pumps are now manufactured and installed. The average pump efficiency between the flow ranges of 500 barrels of fluid per day (BFPD) and 12,000 BFPD is 72% as compared to an average of 64% over similar flow ranges with non-powder metallurgy pumps (Novomet. Power Save Systems. 2016). In addition to power savings, operators are experiencing significant increases in equipment run time with PMMs and powder metallurgy pumps. By producing the required horsepower with reduced current loading, heat rise is reduced. The reduction of heat in electrical components increases run life. PMM systems are also much shorter in length to comparable systems. Less length means less components, higher reliability, and ease of access through high dog leg severities. These advancements are made possible by the extensive testing that occurs at electrical submersible pump research and development centers. The data portrayed in this paper were derived from the Konnas testing facilities in Moscow, Russia, which is a throwback to the Soviet Era when the facility was used for research and development for electronic submersible pumps (ESP). For decades following the 1950's Konnas was responsible for 100% of the ESP pump designs in the former Soviet Union (Novomet, 2018). The test results were validated in over 1,000 wells across Russia, Egypt, Colombia, Argentina, Canada, Venezuela, and the United States. This paper provides an in-depth view of efficiency losses down to individual components; how these losses are mitigated; and how this technology affects the economics of a well. This paper includes actual "before and after" well data from Tribal C-20 in the Wind River Basin of Wyoming. A PMM/powder metallurgy stage versus AM/cast stage system comparison of an actual well was economically analyzed to show the extension on the economic life of the well including the decrease in operating expense (OPEX) and the increase in reserves. Many similar tests were recently conducted within this region and the average electrical savings equaled 30%. In this case, the power savings were on par with average savings of 27%. The electrical OPEX was decreased by $5,460.34 USD per month. From these savings the economical limit of the well increased; hence, the revenue, profit, and reserves increased along with the overall asset value.

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: Empirical
Teacher disagreement score0.534
Threshold uncertainty score0.880

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 head0.024
GPT teacher head0.241
Teacher spread0.217 · 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

Citations7
Published2018
Admission routes1
Has abstractyes

Explore more

Same topicOil and Gas Production TechniquesFrench-language works237,207