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Record W3040857342 · doi:10.1029/2020gl087999

Nanoconfined Water Effect on CO<sub>2</sub> Utilization and Geological Storage

2020· article· en· W3040857342 on OpenAlexaff
Kaiqiang Zhang, Lirong Liu, Guohe Huang

Bibliographic record

VenueGeophysical Research Letters · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsCaprockOil shalePetroleum engineeringMaterials scienceIntermolecular forcePermeability (electromagnetism)Environmental scienceChemical engineeringSoil scienceChemical physicsGeologyChemistryMoleculeOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Understanding nanoconfined water effect on CO 2 utilization and storage has tremendous implications in academic research and practical applications, especially for extremely low‐permeability shale reservoirs. Here, a new nanoscale‐extended cubic‐plus association equation of state is developed by including the confinement effects and intermolecular interactions, based on which the phase behavior and interfacial tension of the pure water and water‐CO 2 system are accurately calculated. Moreover, three important parameters, caprock‐sealing pressure, maximum storage height, and storage capacity, are quantitatively determined for assessing the potential for the CO 2 storage. On the basis of the results from this study, the negative effect of nanoconfiend water can be substantially reduced or even converted to be positive for the CO 2 utilization and storage in the shale reservoirs due to the extremely small pore scale as well as the associated strong confinements and intermolecular interactions. Overall, this study supports the foundation of general practical applications pertaining to CO 2 utilization and geological storage in unconventional low‐permeability shale formations with existence of nanoconfined water.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.125
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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)0.0010.004

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 head0.049
GPT teacher head0.319
Teacher spread0.269 · 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; both teacher heads agree on what is shown here.

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

Citations29
Published2020
Admission routes1
Has abstractyes

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