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Record W1873098207 · doi:10.3968/6291

Investigation on Actuating Pressure Gradient of Low Permeability Reservoir

2015· article· en· W1873098207 on OpenAlexvenueno aff
Zhao Chun-sen, Didi Wu, Tao Bo

Bibliographic record

VenueAdvances in petroleum exploration and development · 2015
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPressure gradientPermeability (electromagnetism)PorosityMaterials scienceViscosityPorous mediumMechanicsComposite materialChemistryMembranePhysics

Abstract

fetched live from OpenAlex

Due to the presence of actuating pressure of low permeability reservoir, researching on actuating pressure gradient of low permeability reservoir is necessary. While actuating pressure gradient is relevant to permeability and porosity, it can be obtained through laboratory experiments, well testing interpretation method and theory derivation combined with practical application method. The results of a large number of laboratory experiments show that actuating pressure is related to permeability. The greater the permeability is, the smaller the actuating pressure is. They both present the similar hyperbolic relationship; the greater the viscosity of the oil is, the greater the actuating pressure is. Here, we get the actuating pressure gradient formula through the method of theory derivation combined with practical application, meanwhile we put forward the relationship between actuating pressure gradient and permeability, porosity and viscosity. Key words: Low permeability reservoir; Actuating pressure gradient; Porosity; Fluid viscosity

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.040
GPT teacher head0.260
Teacher spread0.220 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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