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Record W2077996925 · doi:10.2118/0708-0064-jpt

Technology Focus: Artificial Lift (July 2008)

2008· article· en· W2077996925 on OpenAlexaboutno aff
Stuart Scott

Bibliographic record

VenueJournal of Petroleum Technology · 2008
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsArtificial liftPetroleum engineeringSteam injectionLift (data mining)Gas liftSucker rodEngineeringMultiphase flowOil wellEnvironmental scienceMechanical engineeringComputer scienceMechanics

Abstract

fetched live from OpenAlex

Technology Focus Artificial lift plays a fundamental role in several international plays. This month, artificial lift in oil-sand and deepwater developments is highlighted. In both cases, artificial lift is not just accelerating production but is vital to the economic success of the overall development. Today, the Canadian oil-sand developments have followed these different approaches: mining, cyclic steam injection, and steam-assisted gravity drainage (SAGD). As reservoir depth increases, artificial lift, rather than mining, is used to bring hydrocarbons to the surface. While cyclic steam injection and SAGD both push the high-temperature envelope for pumping, new techniques are being proved for this harsh environment. During the production phase of cyclic steam injection, the wells initially flow to the surface. Later production moves into the "flumping" stage (simultaneous flowing and pumping) and then into pumping. While sucker-rod pumping has been dominant, progressing-cavity pumps and electrical submersible pumps (ESPs) are being proved under these extreme conditions. In addition to downhole pumping, there is widespread use of surface multiphase pumps. Technologies that allow pumping high-temperature fluids without cooling represent opportunities to retain heat and improve the overall process efficiency. Surface pumping of a high-temperature multiphase mixture has become an established technology in Alberta. For deep water, artificial lift plays a strategic role, enabling companies that possess advanced technology to develop fields that other companies may determine to be too difficult. The ability to deliver an advanced artificial-lift system is the difference between booking reserves and walking away from deepwater discoveries. Only recently have we seen rapid growth in the application of subsea multiphase pumping. In addition to seafloor boosting, several other artificial-lift methods are applied in deep water, including gas lift and wellbore ESPs. In all cases, the ultimate success of these developments depends on the reliability of the artificial-lift system combined with the cost of intervention. Artificial Lift additional reading available at the SPE eLibrary: www.spe.org SPE 113904 • "Recent Advances and Practical Applications of Integrated Production Modeling at Jack Asset in Deepwater Gulf of Mexico" by Umut Ozdogan, Chevron Energy Technology Company, et al. IPTC 11594 • "A New Approach to Gas Lift Optimization Using an Integrated Asset Model" by Fernando Gutierrez, Schlumberger, et al. SPE 110234 • "Overview of Beam-Pump Operations" by O. Lynn Rowlan, Echometer Company, et al. Additional reading available at OnePetro: www.onepetro.org OTC 18820 • "The Use of Subsea Gas Lift in Deepwater Applications" by Subash S. Jayawardena, Shell Global Solutions, et al. (See JPT June, 2008, page 64.)

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.603
Threshold uncertainty score0.799

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.009
GPT teacher head0.210
Teacher spread0.201 · 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
Published2008
Admission routes1
Has abstractyes

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