Understanding the interactions of NaClO oxidant with coal for intensified hydraulic fracturing effectiveness
Why this work is in the frame
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Bibliographic record
Abstract
The efficacy of hydraulic fracturing coalbeds to enhance methane production suffers from a reduction of the effective permeability due to formation damage. To address this practical challenge, this paper explores the feasibility of applying the oxidative treatment to coals in the post-hydraulic fracturing period. Experimental methodologies are utilized to reveal the fundamental interactions of coal with the oxidative in the context of a combined treatment of hydraulic fracturing and NaClO solution injection. Anthracite and bituminous coals are experimented to account for the effect of coal rank. A comprehensive package of techniques, i.e., ultrasonic wave velocity and hardness (for mechanical properties), scanning electron microscopy (for microstructure and morphology), contact angle (for wettability), and FTIR spectroscopy (for functional groups) were employed to comprehensively investigate the impacts of fracturing fluid and NaClO solution on the chemical and physical properties of the coal samples. The results show that the fracturing fluid exerts varying degrees of harm to the permeability of the two coals, while the effects of oxidative treatment are rank specific in dissolving the blockage and smoothening the fracture surface. It is further unveiled that NaClO solution promotes aromatic structure decomposition at the coal surface to form oxygen-containing functional groups, and its effects on coal permeability evolve in multiple stages. The findings of this study shed light upon implementing oxidative treatment to aid hydraulic fracturing performance in CBM for clean coal production in a carbon-constrained world.
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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