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Record W2998571364 · doi:10.1016/s1876-3804(19)60281-8

Colloidal gas aphron (CGA) based foam cement system

2019· article· en· W2998571364 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePetroleum Exploration and Development · 2019
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsColloidCementMaterials sciencePetroleum engineeringWaste managementChemical engineeringComposite materialGeologyEngineering

Abstract

fetched live from OpenAlex

To solve the problems such as high denstiy, foam instability, low compressive strength, high porosity and poor durability associated with conventional foam cements, a novel colloidal gas aphron (CGA) based foam cement system was investigated and tested for properties. CGA is used in a base slurry as the foam component and the recipe was optimized with hollow sphere and micro-silica in terms of particle size distribution (PSD). Porosity, permeability, strength, brittleness, elasticity, free water content, foam stability and density tests on the CGA based foam cement system were carried out to evaluate the performance of the system. According to the experiment results, at the foam proportion of 10%, the cement density was reduced to 1 040 kg/m3, and stable microfoam net structure not significantly affected by high temperature and high pressure was formed in the cement system. The optimal CGA based foam cement has a free water content of 0%, porosity of 24%, permeability of 0.7×10−3 μm2, low elasticity modulus, high Poisson's ratio, and reasonable compressive strength, and is more elastic and flexible with capability to tolerate regional stresses.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.798
Threshold uncertainty score0.665

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 head0.009
GPT teacher head0.169
Teacher spread0.159 · 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