Insights into the fluid wetting law and fractal characteristics of coal particles during water injection based on nuclear magnetic resonance

He Yang, Zhen Liu, Dawei Zhao, Jialu Lv and Wenzhi Yang

Chaos, Solitons & Fractals, 2022, vol. 159, issue C

Abstract: In order to reveal the migration mechanism of dynamic water between coal particles in the process of coal seam water injection, in this study, nuclear magnetic resonance experiments (NMR) were carried out on wetted coal samples, the transverse relaxation time (T2) spectra of samples presenting different degrees of metamorphism and particle size ranges were measured over different time periods of the wetting process, and the fractal dimension (DNMR) of the wetting phase distribution in the migration channel was calculated. (1) The average values of T2g decrease percentage Δ of the three coal samples are 84%, 71.25%, and 57.75%, indicating that the order of the wettability strength is Daliuta coal sample (DLT) > Xinglongzhuang coal sample (XLZ) > Qincheng (QC), this shows that the coal samples are more easily wetted as the degree of metamorphism decreases. (2) Sodium dodecyl sulfate (SDS) will make the wetting process between coal and water smoother, and in the range of 60–80 mesh and 100–120 mesh particle size, compared to the solution properties change, the particle size has relatively little influence on the wetting process when its change is not large. (3) The surface tension reduction caused by the addition of surfactants in the water, the narrowing of the pore space caused by the reduction of the overall size of the particles, and the decrease of the particle surface wettability caused by the increase in the metamorphic degree of coal sample will lead to the decrease of DNMR measured in the experiment. Based on the above research, it can provide a theoretical basis for improving the effect of coal seam wetting and dust reduction.

Keywords: Coal seam water injection; Nuclear magnetic resonance; Wetting; Fractal (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:159:y:2022:i:c:s0960077922003198

DOI: 10.1016/j.chaos.2022.112109

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