Modified Dubinin–Astakhov Model for the Accurate Estimation of Supercritical Methane Sorption on Shales
Bibliographic record
Abstract
In order to evaluate the total shale gas-in-place (GIP) resources in deep formations, it is important to study the sorption of supercritical methane in shales. At present, the Dubinin–Astakhov model is used to describe sorption isotherms. However, it still has some shortcomings. The main objective of this study is to establish an optimized model for supercritical methane sorption in shales. A series of high-pressure methane sorption isotherms were measured at different temperatures (from 293 to 333 K) for shale samples collected in the Cengong block, Guizhou, China. The characteristics and causes of shale gas sorption capacity changes were analyzed. By comparing the fitting results of several conventional sorption models, the characteristics and applicable scope of these models are obtained. A four-parameter (V0, D, m, and ρa) modified supercritical D–A model was developed to accurately estimate the sorption of supercritical methane on shales based on Polanyi sorption potential theory. The results show that the sorption characteristic curve of methane on the shale surface under high pressure is obviously different from that under low pressure. The density of the sorption phase and the virtual saturated vapor pressure have a great influence on the fitting results of the sorption models. The density of the adsorption phase directly determines the ultimate sorption capacity of the shale sample. Also, the modified D–A model can improve the accuracy of the prediction of supercritical methane sorption on shales, and it can accurately describe the isothermal sorption law of gas in the supercritical state.
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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".