Adsorption Characteristics of CO2/CH4/H2S Mixtures in Calcite Nanopores with the Implications for CO2 Sequestration
Bibliographic record
Abstract
Summary Injecting CO2 into reservoirs for storage and enhanced oil recovery (EOR) is a practical and cost-effective strategy for reducing carbon emissions. Commonly, CO2-rich industrial waste gas is used as the CO2 source, whereas contaminants such as H2S may severely impact carbon storage and EOR via competitive adsorption. Hence, the adsorption behavior of CH4, CO2, and H2S in calcite (CaCO3) micropores and the impact of H2S on CO2 sequestration and methane recovery are specifically investigated. The Grand Canonical Monte Carlo (GCMC) simulations were applied to study the adsorption characteristics of pure CO2, CH4, and H2S, and their multicomponent mixtures were also investigated in CaCO3 nanopores to reveal the impact of H2S on CO2 storage. The effects of pressure (0–20 MPa), temperature (293.15–383.15 K), pore width, buried depth, and gas mole fraction on the adsorption behaviors are simulated. Molecular dynamics (MD) simulations were performed to explore the diffusion characteristics of the three gases and their mixes. The amount of adsorbed CH4, CO2, and H2S enhances with rising pressure and declines with rising temperature. The order of adsorption quantity in CaCO3 nanopores is H2S > CO2 > CH4 based on the adsorption isotherm. At 10 MPa and 323.15 K, the interaction energies of CaCO3 with CO2, H2S, and CH4 are −2166.40 kcal/mol, −2076.93 kcal/mol, and −174.57 kcal/mol, respectively, which implies that the order of adsorption strength between the three gases and CaCO3 is CO2 > H2S > CH4. The CH4-CaCO3 and H2S-CaCO3 interaction energies are determined by van der Waals energy, whereas electrostatic energy predominates in the CO2-CaCO3 system. The adsorption loading of CH4 and CO2 are lowered by approximately 59.47% and 24.82% when the mole fraction of H2S is 20% at 323.15 K, reflecting the weakening of CH4 and CO2 adsorption by H2S due to competitive adsorption. The diffusivities of three pure gases in CaCO3 nanopore are listed in the following order: CH4 > H2S ≈ CO2. The presence of H2S in the ternary mixtures will limit diffusion and outflow of the system and each single gas, with CH4 being the gas most affected by H2S. Concerning carbon storage in CaCO3 nanopores, the CO2/CH4 binary mixture is suitable for burial in shallower formations (around 1000 m) to maximize the storage amount, while the CO2/CH4/H2S ternary mixture should be buried as deep as possible to minimize the adverse effects of H2S. The effects of H2S on CO2 sequestration and CH4 recovery in CaCO3 nanopores are clarified, which provides theoretical assistance for CO2 storage and EOR projects in carbonate formation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".