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Record W2506386344

Sand Production Rate Under Multiphase Flow And Water Breakthrough

2010· article· en· W2506386344 on OpenAlexaff
E. Päpamichos, Pierre Cerasi, J. F. Stenebråten, A. N. Berntsen, I. Ojala, I. Vardoulakis, M. Brignoli, G.-F. Fuh, Gang Han, Asaf Nadeem, Pascal Ray, Sturla Wold

Bibliographic record

VenueDSpace - NTUA (National Technical University of Athens) · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsConocoPhillips (Canada)
Fundersnot available
KeywordsProduction (economics)Environmental scienceFlow (mathematics)Multiphase flowPetroleum engineeringGeologyEconomicsMechanics
DOInot available

Abstract

fetched live from OpenAlex

The sand production rate in three outcrop sandstones under various saturation and flow fluids is investigated to reveal the potential contribution of three different mechanisms on sand production rate and initiation. The mechanisms that are investigated are strength water weakening, capillary cohesion in the failed zone and the pore pressure gradient front during water breakthrough. The sand production experiments are designed such that the relevant importance of each mechanism can be identified. Thus for each sandstone four sand production test types are performed and compared. Two of the test types are with one-phase flow and two are with two-phase flow including water breakthrough tests. The three tested sandstones are considered analogues of hydrocarbon reservoirs and represent all three borehole failure classes generalizing thus the applicability of the results which show that all mechanisms are important and have to be considered in the development of relevant sand production quantification models. Copyright 2010 ARMA, American Rock Mechanics Association.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.013
GPT teacher head0.202
Teacher spread0.189 · 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 designObservational
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

Citations20
Published2010
Admission routes1
Has abstractyes

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