A developed dual-site Langmuir model to represent the high-pressure methane adsorption and thermodynamic parameters in shale
Bibliographic record
Abstract
Abstract Comprehending the mechanism of methane adsorption in shales is a crucial step towards optimizing the development of deep-buried shale gas. This is because the methane adsorbed in shale represents a significant proportion of the subsurface shale gas resource. To properly characterize the methane adsorption on shale, which exhibits diverse mineral compositions and multi-scale pore sizes, it is crucial to capture the energy heterogeneity of the adsorption sites. In this paper, a dual-site Langmuir model is proposed, which accounts for the temperature and pressure dependence of the density of the adsorbed phase. The model is applied to the isothermals of methane adsorption on shale, at pressures of up to 30 MPa and temperatures ranging from 40 to 100 °C. The results show that the proposed model can describe the adsorption behavior of methane on shale more accurately than conventional models, which assume a constant value for the density of adsorbed phase. Furthermore, the proposed model can be extrapolated to higher temperatures and pressures. Thermodynamic parameters were analyzed using correctly derived equations. The results indicate that the widely used, but incorrect, equation would underestimate the isosteric heat of adsorption. Neglecting the real gas behavior, volume of the adsorbed phase, and energy heterogeneity of the adsorption sites can lead to overestimation of the isosteric heat of adsorption. Furthermore, the isosteric heat evaluated from excess adsorption data can only be used to make a rough estimate of the real isosteric heat at very low pressure.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".