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Record W2077249686 · doi:10.2118/165578-pa

Quantifying Heat Requirements for SAGD Startup Phase: Steam Injection, Electrical Heating

2013· article· en· W2077249686 on OpenAlex

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

VenueJournal of Canadian Petroleum Technology · 2013
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsLaricina Energy (Canada)Canadian Natural Resources
Fundersnot available
KeywordsWellboreHeat transferSteam injectionHeat fluxPetroleum engineeringSteam-assisted gravity drainageConstant (computer programming)Process (computing)EngineeringNuclear engineeringTransient (computer programming)MechanicsMechanical engineeringMaterials scienceComputer scienceOil sands

Abstract

fetched live from OpenAlex

Summary A proper and effective startup of the steam-assisted-gravity-drainage (SAGD) well pairs, where both horizontal wells inject steam, is a key parameter to SAGD performance. In the past, a number of investigations have been conducted on the optimum startup strategy and operational procedures; however, fewer studies have modelled the heat requirements of the process. This study proposes an effective practical method that correlates the heat flux inside the horizontal wellbore with the temperature outside the wellbore wall. A transient conductive-heat-transfer equation in a cylindrical coordinate system is adopted for two different startup strategies: (a) variable heat flux (steam circulation in the well pair) to maintain a constant desired temperature at the wellbore wall and (b) constant heat flux (electrical heating of the well pair) to gradually increase temperature and finally reach a desired temperature on the wellbore wall. A novel and simple mathematical technique is presented for each startup approach to evaluate the instantaneous and cumulative heat requirements to keep the wellbore hot. Excellent agreements between the results of the proposed techniques and outputs of a commercial reservoir simulator are demonstrated. Accurate quantitative evaluation of heat requirements for the startup phase of SAGD enables optimum planning for steam requirements and practical design of any other heat sources employed in the process.

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 score0.088
Threshold uncertainty score0.657

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
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 head0.032
GPT teacher head0.300
Teacher spread0.268 · 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