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Record W1976810927 · doi:10.1029/2000wr900316

Measurement of aperture distribution, capillary pressure, relative permeability, and in situ saturation in a rock fracture using computed tomography scanning

2001· article· en· W1976810927 on OpenAlexaff
Stephanie P. Bertels, David A. DiCarlo, Martin J. Blunt

Bibliographic record

VenueWater Resources Research · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsGolder Associates (Canada)
FundersU.S. Department of Energy
KeywordsCapillary pressureRelative permeabilitySaturation (graph theory)Capillary actionMaterials scienceWettingPermeability (electromagnetism)In situComposite materialWater saturationTomographyMineralogyGeologyGeotechnical engineeringOpticsChemistryPorous mediumPorosity

Abstract

fetched live from OpenAlex

We develop an experimental technique that uses computed tomography (CT) scanning to provide high‐resolution measurements of aperture distribution and in situ saturation along with capillary pressure and relative permeability for the same rough‐walled fracture. We apply this technique to an induced fracture in a cylindrical basalt core undergoing water drainage. We find that the sum of the water and gas relative permeabilities is much <1 at intermediate saturations and the water relative permeability shows a sharp change over a narrow range of average water saturation. In situ saturation maps show channeling of gas and significant retention of the wetting phase (water). The capillary pressure initially increased and then decreased with decreasing water saturation. Although this type of capillary behavior is atypical for unsaturated flows, we find that the sizes of the gas‐filled apertures are consistent with the measured capillary pressure.

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)0.001
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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.036
GPT teacher head0.282
Teacher spread0.246 · 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

Citations191
Published2001
Admission routes1
Has abstractyes

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