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Record W2037751074 · doi:10.2118/138104-ms

Investigation of Anisotropic Behavior of Montney Shale Under Indirect Tensile Strength Test

2010· article· en· W2037751074 on OpenAlexafffundabout
S.A.R. Keneti, R.C.K. Wong

Bibliographic record

VenueCanadian Unconventional Resources and International Petroleum Conference · 2010
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsUltimate tensile strengthAnisotropyGeologyOil shaleHydraulic fracturingGeotechnical engineeringCompressive strengthMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Abstract Located in a large area spanning the British Columbia and Alberta border, the Montney shale formation is one of the largest economically feasible resource plays in North America. Hydraulic Fracturing is one of the stimulation methods to enhance the gas production in which fractures induced by hydraulic loading are created. Initiation and propagation of hydraulically induced fracture is controlled by in-situ stresses magnitude and orientation and the reservoir tensile strength. If the in-situ stresses composing one vertical and two horizontal stresses are comparable or lie within a narrow range, the tensile strength becomes one of the most important parameters in governing hydraulic fracturing of the reservoir. This paper develops different point and line load tests to determine the tensile strength of Montney shale cores in two perpendicular directions. Test results indicate that Montney shale exhibits a high anisotropy in tensile strength. The tensile strength in the horizontal direction is dominated by the bond strength of the intact structure whereas that in the vertical direction is controlled by the existence of the natural beddings (foliations). This paper also addresses how this anisotropy in tensile strength could affect the pattern of hydraulically induced fractures in the field.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.620
Threshold uncertainty score0.994

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 head0.022
GPT teacher head0.215
Teacher spread0.193 · 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

Citations16
Published2010
Admission routes3
Has abstractyes

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