Quantitative Characterization of Mineral Properties and Microstructures in Deep Coal-Rock
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Bibliographic record
Abstract
Abstract In this study, a comprehensive and practical experimental method was employed to quantitatively characterize mineral properties and microstructure characteristics of deep coal-rock (DCR). Experimentally, core samples were collected from two study areas in a DCR reservoir, and the petrological and mineral characteristics of the DCR were determined by performing proximate analysis, vitrinite reflectance, maceral components, scanning electron microscopy (SEM) and X-ray diffraction (XRD) experiments. Additionally, other tests such as physisorption and high-pressure mercury injection (HPMI) were conducted to quantitatively characterize the nano- to micro-microstructures. The microscopic components of the DCR are primarily composed of vitrinite, followed by inertinite, whereas liptinite and mineral matter occur in comparatively lesser quantities. The storage space within the DCR primarily consists of cellular pores and fractures, with the majority of these pores being occupied by clay minerals, and the crystalline materials present in the DCR contribute to an increase in the specific surface area of the coal rocks to a certain extent. Although the difference in total pore volume (PV) between the micropores and mesopores of Samples Q and J is relatively minor, such a modest increase in total PV contributes to a substantial rise in specific surface area (SSA), leading to a pronounced discrepancy in SSA between these two types of samples. Despite the presence of microcracks in Sample Q, micropores remain the predominant pore type, contributing over 99% to the SSA, thereby serving as the primary space for adsorbed gas. However, macropores and microcracks significantly contribute to the total PV, providing essential flow channels for desorption, diffusion, and seepage of adsorbed gas. Such quantitatively characterized mineral properties and microstructures of DCR will provide valuable insights for assessing the presence of free gas and adsorbed gas.
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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 | 0.000 | 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 it