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Record W2039656706 · doi:10.2118/150293-ms

Geomechanics for the Thermal Stimulation of Heavy Oil Reservoirs–Canadian Experience

2011· article· en· W2039656706 on OpenAlexafffundabout
Yanguang Yuan, Bin Xu, Baohong Yang

Bibliographic record

VenueSPE Heavy Oil Conference and Exhibition · 2011
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsBitCan (Canada)
FundersAlberta Innovates
KeywordsGeomechanicsCaprockPetroleum engineeringGeologyField (mathematics)Geotechnical engineeringMathematics

Abstract

fetched live from OpenAlex

Abstract This paper will cover both caprock integrity and reservoir deformation, drawing from our years of experience in working with the heavy oil/oilsands industry in Alberta, Canada. Theoretical principles are described, analytical derivations made and field examples given, all to help illustrate the fundamentals and summarize the learnings in proactive utilization of geomechanics to enhance the reservoir performance and proactive consideration of geomechanics to ensure the caprock integrity. Topics include dilation tendency and fracturing behaviour in the oilsands, major geomechanical work components for the caprock integrity analysis/design, mini-frac tests and nonlinear coupled thermo-hydro-mechanical processes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.035
GPT teacher head0.239
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations27
Published2011
Admission routes3
Has abstractyes

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