Experimental Investigations of the Impact of H2, He, CH4, and CO2 Exposure on Kerogen Adsorption, Wettability, and Geomechanical Characteristics at Geo-Storage Conditions
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".