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Record W2020903517 · doi:10.2118/117489-ms

SAGD Gas Lift Completions and Optimization: A Field Case Study at Surmont

2008· article· en· W2020903517 on OpenAlex
T. C. Handfield, T. Nations, Shauna Noonan

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Thermal Operations and Heavy Oil Symposium · 2008
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsConocoPhillips (Canada)
FundersConocoPhillips
KeywordsGas liftLift (data mining)Petroleum engineeringArtificial liftNozzleSluggingEngineeringNatural gas fieldCompletion (oil and gas wells)Natural gasMechanical engineeringEnvironmental scienceMarine engineeringComputer scienceWaste managementMechanicsFlow (mathematics)

Abstract

fetched live from OpenAlex

Abstract Gas lift completions for SAGD1 producers are unique. Conventional gas lift valves and mandrels with a packer completion cannot be used due to the extreme temperatures of the downhole environment. Most lift gas enters the production stream downhole via open-ended tubing or nozzles, which if not properly sized can result in operational issues, such as fluid / gas slugging and pressure instabilities which negatively impact the overall lift efficiency. In 2006, ConocoPhillips conducted a study to design a gas lift system for the Surmont SAGD development that would allow better control of lift gas into the production string and in late 2007 the wells completed with gas lift were placed on production. This paper will cover the data collection effort and analysis completed to determine the efficiency of the two types of gas lift nozzles used in the completions, the methodology for optimization of SAGD gas lift systems and recommendations for future improvement.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.493

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 head0.016
GPT teacher head0.241
Teacher spread0.225 · 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