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Record W2045899134 · doi:10.2118/165457-ms

Modifications to Butler Theory for Geomechanical Effects at the Edge of SAGD Steam Chamber. Part I: Drained Condition

2013· article· en· W2045899134 on OpenAlexaff
Mazda Irani, Ian D. Gates

Bibliographic record

VenueSPE Heavy Oil Conference-Canada · 2013
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPetroleum engineeringSteam injectionSteam-assisted gravity drainageOil sandsPermeability (electromagnetism)GeologyDrainageAsphaltThermalGeotechnical engineeringMaterials scienceChemistryThermodynamicsComposite material

Abstract

fetched live from OpenAlex

Abstract Steam-assisted gravity drainage (SAGD) has been demonstrated to be a successful thermal recovery technique for recovering bitumen from oil sand reservoirs where the viscosity of the bitumen is typically hundreds of thousands to millions of centipoise. High pressure and high temperature steam injection cause significant stress changes at the edge of the steam chamber including shear dilation which, in turn, can enhance the absolute permeability. The importance of considering geomechanical effects in SAGD process has been extensively discussed in the literature but geomechanical effects have been neglected in the classic SAGD analytical models. All analytical models are typically incapable of fully predicting actuall SAGD production rates without using a correction factor; this can be a result of neglecting geomechanical effects. In the research documented here, we examine geomechanical enhancement at the edge of steam chamber where the oil sand has been sheared under thermal stimulation. We describe a mechanism and evaluate the oil drainage parallel to the interface of steam chamber caused by permeability enhancement from thermal stresses. Finally, we present a modified Butler's Theory that includes geomechanical effects. The results are directly applicable to understanding the geomechanical effects on oil drainage flow at the edge of SAGD chamber.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score0.968

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)0.0010.000

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 head0.012
GPT teacher head0.212
Teacher spread0.200 · 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 designNot applicable
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

Citations4
Published2013
Admission routes1
Has abstractyes

Explore more

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