Mechanism of Liquid-Phase Adsorption and Desorption in Coalbed Methane Systems: A New Insight Into an Old Problem
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Bibliographic record
Abstract
Summary Coalbed-methane (CBM) recovery is a process of desorption rather than adsorption. Traditional experimental studies of methane adsorption/desorption on dry or moist coal samples illustrate little hysteresis between adsorption and desorption isotherms. However, coal porosity is always occupied by water in actual conditions, and few researches focus on the gas sorption from water-saturated coals. In such conditions, there is an equilibrium between methane-molecule dissolution into pore water and adsorption on (or desorption from) pore surface, which indicates a typical liquid/solid sorption process rather than gas/solid sorption process. This paper presents experiments with methane adsorption/desorption on coal samples saturated with water. To our surprise, the desorption amount changes slightly with different pressure drops, and the desorption ratio for each of our three sets of experiments is only 3.36, 4.98, and 4.21%, respectively. This dramatic result indicates that sorption from saturated aqueous solution presents significant hysteresis, which considerably differs from a gas-phase sorption case (e.g., sorption on dry or moist samples). On the basis of our theoretical analysis, this hysteresis is caused mainly by additional energy consumed by phase behavior (e.g., nucleation) and capillary resistance in a gas/water/solid system. Further, a unified model is established instead of the traditional Langmuir equation to describe the hysteresis phenomenon between adsorption and desorption from an aqueous environment. Our present work demonstrates that pore water will play a significant role in resisting methane desorption, and the high water saturation in the CBM system will lead to extremely low recovery. Therefore, using the traditional sorption-isotherm curve to predict deliverability of a gas well may result in a large deviation in some cases.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 it