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Record W4392726829 · doi:10.2118/218099-ms

Pore-Scale Investigation of Caprock Integrity in Underground Hydrogen Storage

2024· article· en· W4392726829 on OpenAlexaff
Hai Wang, Shengnan Chen, Peng Deng, Muming Wang, Zhengxiao Xu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCaprockPetroleum engineeringScale (ratio)GeologyEnvironmental science

Abstract

fetched live from OpenAlex

Abstract This study investigates the sealing capacity of shale caprocks for underground storage of hydrogen (H2) utilizing mercury intrusion capillary pressure (MICP) data of caprock samples. The research explores the influence of capillary forces on gas leakage through caprocks and evaluates the effectiveness of caprocks in confining H2 and CO2. Results indicate that the interfacial tension between H2 and water/brine is significantly higher than that between CO2 and water/brine, leading to greater column heights for H2 (ranging from 59 to 667 meters) compared to CO2 (ranging from 20 to 500 meters). Additionally, the study reveals that thicker caprock layers significantly reduce the rate of gas leakage, with CO2 exhibiting higher mass leakage rates due to its larger molar mass and lower interfacial tension compared to H2. Furthermore, while the capillary bundle model estimates higher leakage rates, the pore network model, accounting for the shielding effect of small channels, predicts lower leakage rates, demonstrating its potential for more accurate estimations. The findings highlight the potential of shale caprocks as effective barriers for H2 and CO2 storage, emphasizing the importance of capillary forces and caprock thickness in mitigating gas leakage.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0050.000

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 head0.262
Teacher spread0.242 · 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.

Study designObservational
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

Citations8
Published2024
Admission routes1
Has abstractyes

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