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Record W2975180865 · doi:10.2118/195934-ms

Triaxial Testing System for Seismic Frequencies Measurements with Laser Displacement Sensors

2019· article· en· W2975180865 on OpenAlexaff
Chuan Lu, Jakob Brandl, Nathan Deisman, Richard J. Chalaturnyk

Bibliographic record

VenueSPE Annual Technical Conference and Exhibition · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLoad cellSystem of measurementDynamic testingDisplacement (psychology)Geotechnical engineeringDynamic loadingAnisotropyMaterials scienceSeismic loadingGeologyShear (geology)Dynamic load testingTriaxial shear testStructural engineeringEngineeringComposite materialOptics

Abstract

fetched live from OpenAlex

Abstract In this study, a novel experimental system has been developed for static and dynamic elastic properties measurements at seismic frequencies under anisotropic stress and shear deformation conditions. This system focuses on static and seismic range frequencies dynamic (0.1 Hz to 20 Hz) elastic deformation properties of poorly consolidated oil sands and highly overconsolidated (clay) shales. The main body of the experimental system is a computer control servo-hydraulic system. A pair of laser displacement sensors measure nanometer scale displacement during the dynamic tests. A coarse scale and fine scale load cell system was developed for measuring force with high precision during dynamic testing. A novel triaxial cell for use with the loading system was also developed to simulate the reservoir stress and pore pressure condition during static and dynamic testing and allows permeability to be measured during testing. The loading system, dual load cell calibration procedure and results, and results for acrylic and 3D printed sand specimens are presented. The stable and reasonable results demonstrate the capacity of the new experimental system.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.042
GPT teacher head0.240
Teacher spread0.198 · 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 designBench or experimental
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

Citations2
Published2019
Admission routes1
Has abstractyes

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Same venueSPE Annual Technical Conference and ExhibitionSame topicSeismic Imaging and Inversion TechniquesFrench-language works237,207