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Record W2158816045 · doi:10.2118/75715-ms

General Correlation for the Effect of Non-Darcy Flow on Productivity of Fractured Wells

2002· article· en· W2158816045 on OpenAlexaff
A. Settari, Arthur Bale, R. C. Bachman, V. Floisand

Bibliographic record

VenueSPE Gas Technology Symposium · 2002
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDimensionless quantityPermeability (electromagnetism)TurbulenceGeologyMechanicsFracture (geology)Flow (mathematics)Geotechnical engineeringPetroleum engineeringPhysicsChemistry

Abstract

fetched live from OpenAlex

Abstract The paper describes a systematic study of the effect of the turbulence on productivity (or injectivity) of fractured wells. It extends significantly beyond previous work, and shows its limitations. A new correlation has been developed, based on over 2,000 high-accuracy numerical solutions for vertically fractured well for a simple geometry. The base correlation was developed for fully penetrating fracture and it is applicable to liquid and high-pressure gas systems. The general correlation for fully penetrating fracture is a function of the two dimensionless parameters and two other parameters, which can be chosen as fracture conductivity and permeability. Additional results are provided for the effect of partial perforations on a fully penetrating fracture. As a limiting case, this scenario can represent also transversely fractured horizontal well. The final correlation therefore involves 5 variables. The results show that the conventional notion that turbulence is important only in high rate gas wells is often false. Turbulence effect on productivity or injectivity can be significant for liquid flow in high permeability formations, with limited perforations and especially in transversely fractured horizontal wells.

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 score0.477
Threshold uncertainty score0.424

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 head0.003
GPT teacher head0.201
Teacher spread0.197 · 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

Citations22
Published2002
Admission routes1
Has abstractyes

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