Ma, Shouye and Rangabhashiyam, S (2022) Selection of Characteristic Particle Size of Drilling Cuttings Based on Adsorption-Desorption Properties: Experiment and Simulation. Adsorption Science & Technology, 2022. pp. 1-19. ISSN 0263-6174
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Abstract
The direct method for measuring gas content based on image processing, that is, comparing the desorption curves of drilling cuttings with the characteristic particle size with the desorption image in the database to determine the gas content of coal seams, can solve the problems of long measurement time and larger measurement errors of the traditional direct method. However, the precondition to realize this method is to define the characteristic particle size of drilling cuttings. Therefore, this paper performed adsorption and desorption experiments under different particle size ranges and dissimilar adsorption equilibrium pressures, solved the gas migration control equation in coal particles, and determined the characteristic particle size from experimental results and simulation effect. The results showed that gas desorption quantity was positively correlated with adsorption equilibrium pressure, while negatively correlated with the size of a particle size range. The greater the adsorption equilibrium pressure, the better the linear fitting relationship with the maximum desorption quantity, and the maximum correlation coefficient could reach 0.9658. Based on Darcy’s law, Langmuir adsorption equation, and mass conservation law, the theoretical control equation of gas migration in coal particles was derived and solved by Open source Field Operation and Manipulation (OpenFOAM). The accuracy of the calculation results of the solver was verified by the derived analytical solution of the gas pressure change of coal particles without considering the adsorption. From the experimental results and simulation results, the characteristic particle size of drilling cuttings was determined to be 0.5-1 mm. The research can provide help for the subsequent development of direct gas content measurement technology based on image processing.
Item Type: | Article |
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Subjects: | Academic Digital Library > Engineering |
Depositing User: | Unnamed user with email info@academicdigitallibrary.org |
Date Deposited: | 29 Dec 2022 07:32 |
Last Modified: | 01 Jan 2024 13:03 |
URI: | http://publications.article4sub.com/id/eprint/206 |