In detail analysis of sorption and diffusion kinetics is crucial for designing an accurate model to precisely simulate and predict the gas transportation through coal reservoirs. Earlier research has confirmed that the physio-chemical composition of coal has a significant influence on transportation phenomenon. However, research in this perspective remains elusive. In this work, we provide a detailed framework of pore morphology influence on CO2 adsorption in porous micro structure. The framework encompasses evaluating the pore surface morphology from the 3-D reconstructed geometry of the core processed from CT scan data. Apart from the image analysis, Mercury intrusion porosimetry (MIP) data is used to obtain the pore distribution and permeability.

Keywords:
natural language, coal seam gas, adsorption, Artificial Intelligence, complex reservoir, pore structure, coalbed methane, resolution, coal bed methane, Upstream Oil & Gas
Subjects:
Unconventional and Complex Reservoirs, Coal seam gas
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2019, Unconventional Resources Technology Conference (URTeC)
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