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Study on Matching Ability Between Cement Particle Size and Permeability in the Process of Oil Reservoir Plugging

2012· article· en· W1954479890 on OpenAlexvenueno aff
Qingjie Zhang, Jianguang Wei, Guojun Sun, Liyang Jin, Pengjun Guan

Bibliographic record

VenueAdvances in petroleum exploration and development · 2012
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCementPermeability (electromagnetism)Particle sizeMaterials sciencePetroleum engineeringParticle (ecology)Matching (statistics)Particle-size distributionGeotechnical engineeringComposite materialGeologyEngineeringChemical engineeringChemistryMathematics

Abstract

fetched live from OpenAlex

In order to satisfy the plugging demands of injecting the cement plugging agent into reservoirs with different radial depths, the technical studies of cement particle size optimization should be conducted. Through indoor experiment, the relationship between cement particle size and permeability was investigated by both macroscopic and microcosmic analysis. It is observed that the reservoirs which permeabilities are within 50~200mD are matching well with the cement agents which particle sizes are less than 5μm. And the permeabilities within 200~400mD are matching well with the cement agents which particle sizes are within 5~10μm, the permeabilities within 400~700mD are matching well with the cement agents which particle sizes are within 10~20μm, the permeabilities are above 700mD are matching well with the cement agents which particle sizes are more than 20μm. The plugging success rates of all the matching experiments are exceeding 90%. This research result is important to direct the plugging operation in the field. Key words : Plugging off and channeling prevention; Cement particle size; Permeability; Matching relationship; Experimental study

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.364

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.028
GPT teacher head0.305
Teacher spread0.277 · 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 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

Citations0
Published2012
Admission routes1
Has abstractyes

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