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Record W2037266945 · doi:10.2118/165392-ms

Characterizations on Geomechanical Properties of Colorado Shale Based on Well Logging and Laboratory Testing

2013· article· en· W2037266945 on OpenAlexafffundabout
Biao Li, R.C.K. Wong

Bibliographic record

VenueSPE Heavy Oil Conference-Canada · 2013
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsUniversity of Calgary
FundersMitacsCarbon Management CanadaImperial Oil LimitedYale University
KeywordsOil shaleTransverse isotropyGeologyPoisson's ratioGeotechnical engineeringAnisotropyWell loggingYoung's modulusCohesion (chemistry)StiffnessPetrophysicsIsotropyMineralogyMaterials sciencePetroleum engineeringPoisson distributionComposite materialMathematics

Abstract

fetched live from OpenAlex

Abstract Geomechancial properties of shale are essential to drilling operation and well design for thermal enhanced oil recovery. In this research, well logging and laboratory testing data are integrated to characterize the geomechanial properties of Colorado shale in Cold Lake area, Alberta, Canada. Density and sonic logs were applied to estimate the dynamic deformation modulus, Poisson's ratio, internal frictional angle, and cohesion strength. Gamma ray log is applied to estimate shale's clay content. Triaxial tests and confined torsion tests were conducted on samples to investigate transversely isotropic stiffness parameters and strength at quasi-static condition. The micro fabric characteristics of the clay shale were obtained from SEM images to investigate shale's intrinsic anisotropy. Correlations between geomechanical properties derived from well logging and laboratory testing were generated. Values of deformation modulus and Poisson's ratio derived from laboratory testing and well logging were correlated by introducing empirical coefficients. The anisotropic ratio in rock's Young's modulus is correlated to shale's clay content. The values of log-derived internal frictional angle are consistent with the laboratory tested values. The shale's clay content is found to be an important factor affecting the rock's strength.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.729
Threshold uncertainty score0.686

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)0.0000.000

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 head0.024
GPT teacher head0.177
Teacher spread0.153 · 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 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

Citations4
Published2013
Admission routes3
Has abstractyes

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