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Record W1523689543 · doi:10.3968/6826

Physical Simulation of the Displacement Laws for the Binary Compound Flooding in Offshore Oilfields

2015· article· en· W1523689543 on OpenAlexvenueno aff
NI Ruichong, Erlong Yang, Huijuan Gao, Lan Meili

Bibliographic record

VenueAdvances in petroleum exploration and development · 2015
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPetroleum engineeringBinary numberFlooding (psychology)Submarine pipelineOil fieldDisplacement (psychology)Saturation (graph theory)EngineeringGeologyGeotechnical engineeringMathematics

Abstract

fetched live from OpenAlex

The researches on EOR effects of the binary compound flooding by means of litho-eletric experimental principles and 3D physical simulation system. The pressure meters and resistivity measuring probe installed on the model can accurately detect the changes of the pressure and saturation fields, and then the production effects of the flooding system are evaluated. The experiments show that for heavy oil binary system, the viscosification of the polymer pre-slug and swept volume enlarging role can be fully played. It can not only drive out the remained oil on the main flow lines, but also displace out the remained oil on both sides of the lines through improving the displacement efficiency. After the binary compound flooding, the remained oil mainly exists on the shunt lines among the producing wells. Key words: Binary compound/complex/combined flooding; Litho-electric experiment; Saturation field; Oil displaced effect; 3D physical model

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)0.000
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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.286
Teacher spread0.255 · 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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