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Record W4254745146 · doi:10.31223/osf.io/5sgwz

Cohesive-Zone Effects in Hydraulic Fracture Propagation

2019· preprint· en· W4254745146 on OpenAlexaff
Dmitry Garagash

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsDalhousie University
FundersMinistry of Education and Science of the Russian Federation
KeywordsHydraulic fracturingDissipationMechanicsFracture (geology)Newtonian fluidAsymptoteGeotechnical engineeringFluid dynamicsMaterials scienceLinear elasticityTight gasViscosityGeologyBreakageStructural engineeringComposite materialGeometryThermodynamicsFinite element methodEngineeringPhysicsMathematics

Abstract

fetched live from OpenAlex

Hydraulic fracture presents an interesting case of crack elasticity and fracture propagation non-linearly coupled to fluid flow. Hydraulic fracture (HF) is often modeled using the Linear Elastic Fracture Mechan- ics (LEFM), which assumes that the damaged zone associated with the rock breakage near the advancing fracture front is small compared to the lengthscales of other physical processes acting during propaga- tion. The latter include dissipation in viscous fluid flow in the fracture channel, of which the fluid lag - a region adjacent to the fracture tip filled with fracturing fluid volatiles and/or infiltrated formation pore fluid - is the extreme manifestation. In this study we address the validity of the LEFM approach to hydraulic fracturing by constructing the solution for the near tip region of a cohesive fracture driven by Newtonian fluid in an impermeable linear-elastic rock. We show that the near HF tip solution has an intricate structure supported by a number of nested lengthscales on which different dissipation processes are realized. This structure is bookended by the solid ′c′ or fluid lag ′o′ process zone immediately near the tip and by the viscosity ′m′ asymptote away from the tip, while the LEFM ′k′ asymptote may emerge at intermediate distances within the c/o to m transition. Realization of the k asymptote, and, therefore, the viability of the LEFM in HF, depends on two parameters: the cohesive-to-fluid-lag fracture energy ratio Gc/Go and the cohesive-to-in-situ stress ratio σc/σo. For representative values of the former, we show that the LEFM-behavior emerges only when the cohesive stress is large compared to the in situ confining. Since σc ∼ few MPa for most rocks, it follows that the LEFM may only be applicable to laboratory hydraulic fracture conducted under low confining stress, and, conversely, is not applicable to the field hydraulic fracturing characterized by larger values of σo. We further use an approximate ’equation of motion’ approach based on the continuation of the tip solution onto the entire fracture to solve for the propagation of a penny-shape HF driven by a point source fluid injection and quantify the prominence of the non-LEFM effects.

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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.005
GPT teacher head0.211
Teacher spread0.206 · 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

Citations11
Published2019
Admission routes1
Has abstractyes

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