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Record W4390058171 · doi:10.1021/acs.langmuir.3c02916

Dependence of Methane Transport on Pore Informatics in the Amorphous Nanoporous Kerogen Matrix

2023· article· en· W4390058171 on OpenAlexafffund
Wenhui Li, Yiling Nan, Zhehui Jin

Bibliographic record

VenueLangmuir · 2023
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlliance de recherche numérique du Canada
KeywordsKerogenTortuosityMethaneNanoporousDiffusionAmorphous solidPorosityMaterials sciencePorous mediumChemical physicsMineralogyChemistryThermodynamicsNanotechnologyGeologyComposite materialPhysicsSource rockCrystallographyOrganic chemistry

Abstract

fetched live from OpenAlex

Fluid transport in kerogen is mainly diffusion-driven, while its dependence on pore informatics is still poorly understood. It is challenging for experiments to identify the effect of pore informatics (such as pore connectivity and tortuosity) on fluid transport therein. Therefore, in this work, we use molecular dynamics simulations to study methane transport behaviors in amorphous kerogen matrices with broad pore properties. The pore properties including porosity, pore connectivity, pore size, and diffusive tortuosity are characterized. Next, self-diffusion coefficients in the connected pores ( D eff S ) and in the total pores without distinguishing its connectivity ( D tot S ) are calculated in all the kerogen matrices based on the free volume theory. We find that both D eff S and D tot S exponentially decreases with methane loading with two controlled parameters: fitting constant α eff and D eff S(0) ( D eff S at infinitely small loading) for D eff S and fitting constant α tot and D tot S(0) ( D tot S at infinitely small loading) for D tot S . However, in the kerogen models with relatively low pore connectivity, α eff and α tot as well as D eff S(0) and D tot S(0) can be quite different, inducing the different estimations of D eff S and D tot S . Since methane in the unconnected pores does not contribute to the actual transport, it is important to recognize connected pores when evaluating the fluid transport in kerogen. On the other hand, D eff S(0) strongly depends on the effective limiting pore size ( r lim_eff ) of the dominant flow path and effective diffusive tortuosity (τ eff ), in which D eff S(0) linearly increases with ( r lim_eff /τ eff ) 2 . We also find that α eff is a multivariable function of ϕ eff, τ eff, and r lim_eff, but their generalized relation requires more data to obtain. This work provides important insights into fluid transport in kerogen based on the kerogen pore informatics, which are important to shale gas development.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.014
GPT teacher head0.244
Teacher spread0.230 · 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

Citations4
Published2023
Admission routes2
Has abstractyes

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