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Record W2015022552 · doi:10.1190/1.1567216

Effects of single vertical fluid-filled fractures on full waveform dipole sonic logs

2003· article· en· W2015022552 on OpenAlexaff
Peicheng Xu, Jorge O. Parra

Bibliographic record

VenueGeophysics · 2003
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Waves and Analysis
Canadian institutionsResearch Canada
FundersSouthwest Research Institute
KeywordsBoreholeGeologyFlexural strengthFracture (geology)Discontinuity (linguistics)Sonic loggingAnisotropyGeotechnical engineeringMaterials scienceOpticsPhysicsComposite material

Abstract

fetched live from OpenAlex

Abstract We conducted a parametric study of the effects of single, finite-width, adjacent, vertical, fluid-filled fractures on full-wave borehole dipole logs using the transformed boundary integral equation method. We found that a fracture has significant effects on dipole response if it is within half the wavelength, or two to three times the borehole diameter, from the borehole center. Dual flexural waves and a leaky fracture mode resulted from the waveguide composed of the borehole and fracture. The first flexural wave was controlled by both the borehole and fracture, whereas the second flexural wave was controlled primarily by the borehole but influenced by the fracture. The separation of these two flexural waves increased and the strength of the first one decreased when the distance between the fracture and the borehole increased. The leaky fracture mode was represented by a sharp minimum in the amplitude spectrum, and energy leakage to the fracture reached a maximum when the fracture intersected the borehole. These two unique characteristics distinguish a single fracture from anisotropy. We also estimated location, orientation, and aperture of the fracture through waveform and spectral analyses.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.192
Teacher spread0.186 · 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

Citations35
Published2003
Admission routes1
Has abstractyes

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