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Record W6944659756 · doi:10.20381/ruor-27522

Use of X-ray Absorption Spectrometry to Determine Diffusion Coefficients in Low-Permeability Shale: Queenston Formation Shale

2022· article· en· W6944659756 on OpenAlexaboutno aff

Bibliographic record

VenueuO Research (University of Ottawa) · 2022
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsnot available
Fundersnot available
KeywordsAttenuation coefficientDiffusionAnalytical Chemistry (journal)PorosityCollimated lightOil shaleAbsorption (acoustics)Spectroscopy

Abstract

fetched live from OpenAlex

A new spectrometric technique for measuring diffusion coefficients of Ordovician Queenston Formation shale from the Michigan Basin of southwest Ontario, Canada is presented; in this case pore diffusion coefficients (Dp) were determined for the conservative (iodide, I^-) and reactive (cesium, Cs^+) tracers in porous media. Furthermore, diffusion-reaction parameters such as Cation exchange capacity (CEC) were obtained for the reactive tracer, Cs^+ by the reactive-transport modeling. The principle of X-ray absorption spectrometry (XAS) is based on the attenuation of high atomic number of diffusive species (e.g. Cs^+and I^-) in porous media, allowing for the quantification of the resulting spatial changes. The technique employs a 1.1 mm collimated X-ray beam to resolve the tracer presence in a slice; small region of a rotating sample for a fixed time. The x-ray beam is incident on a sample of porous rock while the transmitted beam is detected on the opposite side of the sample, allowing acquisition of a transmitted X-ray energy spectrum vs intensity (counts). Additional analyses such as mineralogical studies by scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS) were conducted to improve the understanding of solute transport. The comparison of the data obtained by the XAS method indicating a good agreement with established radiography and other conventional diffusion methods provide an alternate approach for quantifying the diffusion coefficient of porous media.

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)0.000
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 score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.042
GPT teacher head0.258
Teacher spread0.216 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

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