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Record W2797130861 · doi:10.7939/r3rx93m2p

Discontinuum Modelling of Vuggy Carbonates

2014· article· en· W2797130861 on OpenAlexaboutno aff
Alma I Ornes

Bibliographic record

VenueUniversity of Alberta Library · 2014
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGeology

Abstract

fetched live from OpenAlex

The Grosmont Formation in Alberta is a heterogeneous carbonate reservoir of current interest for bitumen extraction, specifically within the vuggy porosity unit. The current research addresses the effects of vugs on the strength and stiffness of carbonate samples under uniaxial compression. Particle Flow Code 3D (PFC3D), a discontinuum modelling technique, is used to evaluate vuggy carbonate samples with different vug volumes, shapes, and locations. This thesis also presents a carbonate testing workflow, which combines computed tomography, laboratory testing, and PFC3D modelling. The workflow is evaluated with laboratory experiments on six vuggy carbonate samples from the Grosmont Formation. The workflow successfully generates samples with the correct vuggy geometry; yet the PFC3D simulations over-predict the laboratory results by 24 to 163% for the uniaxial compression strength. Future research on the calibration of PFC3D material for various scales is recommended to further the understanding of up-scaling carbonate properties for heterogeneous reservoirs.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.102
Threshold uncertainty score0.202

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0020.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.147
Teacher spread0.140 · 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 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

Citations0
Published2014
Admission routes1
Has abstractyes

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