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Record W1998802225 · doi:10.2118/150820-pa

Determination of Biot's Effective-Stress Coefficient for Permeability of Nikanassin Sandstone

2012· article· en· W1998802225 on OpenAlexafffundabout
Liping Qiao, R.C.K. Wong, Roberto Aguilera, Apostolos Kantzas

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2012
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaChinese Academy of SciencesUniversity of Calgary
KeywordsBiot numberPermeability (electromagnetism)Effective stressOverburden pressureAnisotropyGeologyPore water pressurePressure coefficientGeotechnical engineeringMineralogyStress (linguistics)MechanicsChemistry

Abstract

fetched live from OpenAlex

Summary In Alberta and British Columbia, a huge amount of tight gas is trapped inrelatively low-permeability rock formations. Physical fracturing of theseformations could enhance the overall formation permeability and thus improvetight gas extraction. One of the outstanding issues in rock fracturing is todetermine the magnitude of applied effective stress. The generaleffective-stress law is defined as seff =sc - asp, where sc andsp are total confining stress and fluid pore pressure,respectively. Each physical quantity of rock responds to total stress and porepressure in a different way, and thus each quantity has its own unique Biot'seffective-stress coefficient. The main objective of this study is toexperimentally determine the Biot's coefficient for permeability of Nikanassinsandstone. A series of permeability measurements was conducted on Nikanassinsandstone core samples from the Lick Creek region in British Columbia undervarious combinations of confining stress and pore pressure. In addition,permeability values were measured both along and across bedding planes toinvestigate any anisotropy in the Biot's coefficient.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.297
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
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 head0.008
GPT teacher head0.220
Teacher spread0.212 · 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 designBench or experimental
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

Citations36
Published2012
Admission routes3
Has abstractyes

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