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Analysis of the Impact of CO<sub>2</sub> Adsorption on Rock Wettability for Geological Storage of CO<sub>2</sub>

2023· article· en· W4386355872 on OpenAlexaff
Jinsheng Wang, Hanin Samara, Vivien Ko, Dustin Rodgers, David Ryan, Philip Jaeger

Bibliographic record

VenueEnergy & Fuels · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsAdsorptionWettingSurface tensionContact angleGravimetric analysisCapillary actionCapillary pressureDrop (telecommunication)ChemistrySessile drop techniqueMineralogyPetroleum engineeringChemical engineeringGeologyMaterials scienceComposite materialThermodynamicsPorous mediumPorosityOrganic chemistry

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide Wettability change of rocks under high-pressure CO 2 is analyzed for CO 2 storage assessment. Increased water contact angle (measured by the sessile drop method) with CO 2 pressure on three different rocks is related to CO 2 adsorption on the rocks using complementary experimental results of CO 2 adsorption (by gravimetric measurement) and interfacial tension between water and CO 2 (by the pendant drop method). An analysis of free energy change accompanying CO 2 adsorption on the rock surface shows that adsorbed CO 2 could result in moving the CO 2 /water/rock contact line and change the rocks from water-wet to non-water-wet, increasing the potential for CO 2 to spread and displace water. The free energy change has not been studied previously, and the results suggest that CO 2 adsorption on rocks could decrease the capillary force in geological reservoirs and enable injected CO 2 to enter a greater portion of pore space. This would significantly increase the reservoir utilization efficiency and CO 2 storage capacity.

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 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 score0.399
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
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 head0.020
GPT teacher head0.283
Teacher spread0.263 · 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 teacher head, 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

Citations16
Published2023
Admission routes1
Has abstractyes

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