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The Development of the New High Temperature Resistance Profile Control Agent Which is Compound With Inorganic Particles and Ge

2014· article· en· W1897236694 on OpenAlexvenueno aff
Chunsheng Wang, Sun Yingfan, Dong Guo-qing, Yu Haoyang, Xu Yujian

Bibliographic record

VenueAdvances in petroleum exploration and development · 2014
Typearticle
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsnot available
Fundersnot available
KeywordsParticle (ecology)Particle sizeMaterials scienceThermal stabilityProcess (computing)Chemical engineeringThermal resistanceThermalThermodynamicsEngineeringComputer science

Abstract

fetched live from OpenAlex

At present, high temperature profile control technology has become the key technology to improving recovery efficiency, management of steam channeling in thermal recovery. The particle of regular application is dosage big, poor injection and easy to cause the rigid block, Gel and foam profile control agent is poor stability, low intensity and short validity period. For the above problems, Developed a new type of high temperature resistance particle-gel complex profile control system through the theoretical analysis and the ratio optimization of indoor experiment and evaluate its performance. The formula of the system: 0.03%Coagulant + 2.2% cross-linking agent I + 1.8%cross-linking agent II + 6% modified high temperature resistance main agent + 0.7% new type inorganic particles + 0.5% suspending agent. At least 280 ℃ of heat-resistant, two-fluid process injection, injection performance is good, the plugging rate is more than 99.05%, scouring resistance and it has good thermal stability. This study provides a new direction for the thermal profile and theoretical basis for profile control construction. Key words : Thermal recovery; Steam channeling; Compound; Profile control agent; Two-fluid process

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.782
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.008
GPT teacher head0.214
Teacher spread0.205 · 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 designNot applicable
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

Citations1
Published2014
Admission routes1
Has abstractyes

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