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Record W4409874204 · doi:10.1016/j.ijggc.2025.104385

Capillary pinning in sedimentary rocks for CO2 storage: Mechanisms, terminology and State-of-the-Art

2025· article· en· W4409874204 on OpenAlexfundno aff
Qin Zhang, S. Geiger, J.E.A. Storms, Denis Voskov, Matthew D. Jackson, Gary J. Hampson, Carl Jacquemyn, Allard W. Martinius

Bibliographic record

VenueInternational journal of greenhouse gas control · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsnot available
FundersEniThe Graduate School, Northwestern UniversityExxon Mobil CorporationEnergi SimulationShellEquinor
KeywordsSedimentary rockTerminologyCapillary actionState (computer science)GeologyMaterials scienceMineralogyGeochemistryPetrologyComposite materialPhilosophyComputer scienceLinguistics

Abstract

fetched live from OpenAlex

Capillary pinning refers to the immobilization of CO₂ at capillary barriers when the uprising CO 2 pressure is lower than the capillary entry pressure of the overlaying pore throats. Also known as local capillary trapping, it has been proposed as a fifth geologic CO₂ storage mechanism, alongside structural, solubility, residual, and mineral trapping. Despite extensive research, the fragmented terminology surrounding capillary pinning has led to confusion, making it challenging to synthesize findings effectively. Often conflated with mechanisms such as residual and hysteresis trapping, capillary pinning is commonly underestimated or completely overlooked in reservoir-scale models. Furthermore, difficulties in characterizing and upscaling small-scale geologic heterogeneities that influence capillary pinning contribute to significant uncertainties, with estimates of CO₂ trapped via this mechanism ranging from 3 % to 100 % of total CO₂ trapped via capillary actions. This review explores the fundamental mechanisms, experimental findings, and modeling approaches for assessing CO₂ capillary pinning in carbon capture and storage (CCS). It seeks to bridge the gap between the reservoir engineering community, with its extensive expertise in hydrocarbon recovery but that needs adjustments for CCS applications, and the subsurface storage community, which stands to benefit from this knowledge but often lacks access to relevant literature. Additionally, the study identifies key research opportunities to advance the understanding of capillary pinning in sedimentary rocks, ultimately enhancing the efficacy and reliability of CCS operations.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.003
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.248
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations7
Published2025
Admission routes1
Has abstractyes

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