Joint response of coal permeability and wettability to changes in organic matter induced by oxidation treatment
Bibliographic record
Abstract
Oxidation treatment can enhance the permeability of coal, but several coal samples are accompanied by increased hydrophilicity after oxidation, showing negative effects on long-term coalbed methane (CBM) production. The “high-quality” coal with significantly high permeability enhancement and decreased/smaller increased hydrophilicity after oxidation apparently obtains higher benefits under similar conditions. Changes in organic matter induced by oxidation treatment provide part of the driving force for the variations in permeability and wettability, but the coals with similar changes in functional groups and opposite oxidation effects are reported in current studies. To determine the joint response of coal permeability and wettability to changes in organic matter after oxidation, permeability/pore and molecular structures/wettability experiments are conducted on eight samples collected from mines in CBM exploitation hotspots in China. The results show that the permeability under varying effective stress increases after oxidation, and the average change in the initial permeability (stress-free conditions, k0) and contact angle (θ) is 65.8% and −40.9%, respectively. However, the change in k0 poorly correlates with the change in θ, and the absolute value of the ratio of the change in k0 and θ (\begin{document}$\left| {\dfrac{{{C_{{k_0}}}}}{{{C_\theta }}}} \right| $\end{document}) ranges from 0.2 to 4.2. When the oxidants are injected into coal, new pores and fractures are formed during organic matter dissolution, directly leading to permeability and total porosity enhancement., and the change in k0 increases with the change in porosity. Moreover, part of the fat and hydroxyl are oxidized to form oxygen-containing functional groups with different polarities, which is the fundamental reason for the differences in the oxidation effects. \begin{document}$\left| {\dfrac{{{C_{{k_0}}}}}{{{C_\theta }}}} \right| $\end{document} is negatively correlated with changes in fat, carboxylic acid, and the absolute value of the ratio of the changes in carboxylic acid to fat. The oxidation effects can be preliminary assessed based on the change in organic matter, and when the fat reduction exceeds 20% and the absolute value of the ratio of carboxylic acid to fat is less than 0.5, \begin{document}$\left| {\dfrac{{{C_{{k_0}}}}}{{{C_\theta }}}} \right| $\end{document} is greater than 2, indicating that the hydrophilicity change is relatively mild compared with the marked permeability enhancement.
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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 | 0.000 | 0.001 |
| 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) | 0.003 | 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".