Modeling of Methane/Shale Excess Adsorption Under Reservoir Conditions
Bibliographic record
Abstract
Summary Micropores and mesopores are the main storage volumes in shale matrix. Because of their small pore sizes, the force between pore boundary and gas molecules is significant. A larger amount of adsorbed gas is in a shale gas reservoir than in a conventional gas reservoir. People usually measure adsorption through volumetric methods under an isothermal condition. Because of a limitation of volumetric methods, only excess adsorption data are directly measured; then, a chosen model is applied to calculate an absolute adsorption through fitting the measured data. An adsorption process induces changes in free-gas volume. However, the changes in absorbent volume and methane absorption into organic matter also alter the measured gas volume, which is widely neglected in previous studies. In this study, one volume term, which accounts for the unexpected changes in gas volumes caused by the other mechanisms except adsorption, is added to the Dubinin-Astakhov (DA) model (pore-filling theory). The in-situ methane is in a supercritical condition under reservoir conditions. Because of the lack of a saturation pressure of a supercritical fluid, an adsorbed-phase gas density is used to replace the saturation pressure in the DA model. The modified model is validated by the isothermal adsorption data from four different shale plays. The calculated data by the proposed model have a better match with the measured data than those by the DA model. All shale samples demonstrate a nonmonotonic deformation of adsorbent (volume shrinkage in the low-pressure region, then swelling as pressure increases), which coincides with the results of previous molecular simulation. The key parameters of the proposed model such as a maximum adsorption capacity are more accurate and reasonable than the ones of the DA model. The proposed model provides a good approach to quantify absolute adsorption through experimental data, especially under reservoir conditions, and to emphasize the important effects of volume on methane/shale adsorption.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".