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Record W2984767493 · doi:10.2118/198699-ms

Evaluating Temperature Rate near the Wellbore Considering Slow Warm-Up Case for a Sagd Producer Well with Different Completion Configurations Using Dynamic Flow Simulations

2019· article· en· W2984767493 on OpenAlexaff
Carlos Nascimento, Barkim Demirdal, Joshua Gauthier

Bibliographic record

VenueSPE Thermal Well Integrity and Design Symposium · 2019
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsCanadian Natural Resources
Fundersnot available
KeywordsCasingCompletion (oil and gas wells)Petroleum engineeringWellboreString (physics)MechanicsFlow (mathematics)Volumetric flow rateTransient (computer programming)Work (physics)Steam injectionOil wellEngineeringMechanical engineeringComputer scienceMathematicsPhysics

Abstract

fetched live from OpenAlex

Abstract Temperature and pressure changes are drastic during the warm-up phase (steam circulation) of SAGD wells as a result of introducing heat to cold tubulars. These drastic changes will impact casings as well as cement. Impacts of circulation strategy (fast vs. slow warm-up) for 11 ¾ in. intermediate casing with dual parallel completion design, on cement and casing were investigated previously. Current work focused on analyzing the impact of slow warm-up on smaller intermediate casing size (9 5/8 in.) for dual parallel and single string completion designs, the second one with vacuum insulation tubing (VIT). The purpose of this paper is to complement the results of previous work in terms of using transient analysis to assess the impact of warm-up rates. The results of transient flow simulator data together with field data enable determining the effect of the warm-up period on different components of wellbore for different types of completions (small versus large wellbore, single versus dual string, uninsulated versus insulated tubing) from integrity perspective. In this study, the dynamic flow simulations indicated that time for steam to reach the toe was almost the same for the dual string and the single string with VIT. In addition, the single string with VIT design eliminated instabilities in operational parameters (e.g. pressure) observed in the case of dual string. However, the single string with VIT case indicated that the heating rate of cement between the intermediate and surface casing string is the highest.

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 categoriesMeta-epidemiology (narrow)
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 score0.261
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.033
GPT teacher head0.267
Teacher spread0.233 · 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.

Study designSimulation or modeling
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

Citations1
Published2019
Admission routes1
Has abstractyes

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