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Record W4409149197 · doi:10.2118/225446-pa

Experimental Investigations of the Impact of H2, He, CH4, and CO2 Exposure on Kerogen Adsorption, Wettability, and Geomechanical Characteristics at Geo-Storage Conditions

2025· article· en· W4409149197 on OpenAlexaff
Bin Pan, Tawanda Matamba, Xia Yin, Mingshan Zhang, Yun Yang, Yongfei Yang, Xianzhi Song, Christopher R. Clarkson, Maxim Lebedev, Katriona Edlmann, Alireza Keshavarz, Stefan Iglauer

Bibliographic record

VenueSPE Journal · 2025
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsKerogenWettingPetroleum engineeringAdsorptionGeologyGeochemistryMineralogyMaterials scienceChemistryComposite materialSource rockGeomorphologyOrganic chemistry

Abstract

fetched live from OpenAlex

Summary Kerogen is the most abundant form of organic matter in the subsurface and its properties of adsorption, wettability, and geomechanics affect gas (H2, He, CH4, and CO2) geo-storage (GGS) capacity and leakage risk. However, the impact of H2, He, CH4 and CO2 exposure on kerogen adsorption, wettability and geomechanical characteristics at in-situ GGS conditions is still unclear, and thus large uncertainties exist in evaluating on GGS integrity. Therefore herein, kerogen properties were investigated experimentally at GGS conditions, based on isothermal adsorption, contact angle, and nanoindentation measurements. It is demonstrated that (1) the maximum adsorption capacity for H2, CH4, and CO2 is 0.3789, 3.5360, and 5.2625 mol/kg, respectively (occurring at various thermophysical conditions), thus following the order H2 < CH4 < CO2; (2) kerogen wettability ranges from weakly water-wet to gas-wet with its affinity to gases following the order He < CO2 < H2 < CH4; and (3) after exposure to H2, He, CH4, and H2O for 3 minutes and to liquid CO2 for 5 minutes, the Young’s modulus of kerogen decreases by 45, 32, 1, 50, and 70% respectively, while the kerogen pellet disintegrates after exposure to supercritical CO2 for 3 minutes. This study provides key data for evaluating GGS, an important pathway for accelerating the energy transition, promoting advanced technology development, balancing the energy supply and demand, and mitigating carbon emissions.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.599
Threshold uncertainty score0.276

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)0.0000.000

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 head0.011
GPT teacher head0.260
Teacher spread0.248 · 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

Citations8
Published2025
Admission routes1
Has abstractyes

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