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Record W4243212378 · doi:10.2118/106243-ms

A New Technical Standard Procedure to Measure stimulation and Gravelpack Fluid Leakoff under Static Conditions

2007· article· en· W4243212378 on OpenAlexaff
M. Asadi, Glenn Penny, Brain Ainley, David Archacki, F. Bas van der, P. A. Bern, Harold Brannon, S. Cobianco, Ali Ghalambor, Paul McElfresh, D. Milton-Tayler, Miles Parker, Subhash Shah

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsOncolytics Biotech (Canada)
Fundersnot available
KeywordsWell stimulationFracturing fluidPetroleum engineeringFiltration (mathematics)Oil wellCore (optical fiber)Hydraulic fracturingViscosityMeasure (data warehouse)Filter (signal processing)Computer scienceGeologyProcess engineeringMaterials scienceEngineeringReservoir engineeringPetroleumMathematics

Abstract

fetched live from OpenAlex

Abstract A group of industry experts have compiled their years of experiences in developing a new technical standard to measure stimulation and gravel-pack fluid leakoff under static conditions. This method details step-by-step procedure for making fluids and measuring leakoff under static conditions. Stimulation and gravel-pack fluids are defined for the purpose of this technical standard as fluids used to enhance production from oil and gas wells by fracturing or acidizing and fluids used to place filtration media to control formation sand production from oil and gas wells, respectively. The procedure considers filter paper medium, natural core and synthetic core as the three filtering options. The paper also includes step-by-step example calculations of viscosity controlled leakoff coefficient and wall building 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 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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.011
GPT teacher head0.258
Teacher spread0.247 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations2
Published2007
Admission routes1
Has abstractyes

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