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论文类型：会议论文

发表时间：2021-01-22

卷号：37

页面范围：5201-5208

关键字：CO2 storage; Capacity; X-ray CT; Saturation; Pore network

摘要：CO2 storage in deep geological structures is considered to be a promising method for the mitigation of CO2 emission. Estimation of the capacity of a geological reservoir is of great importance. Core level study of CO2 storage mechanism and estimation of CO2 storage capacity at laboratory scale have shown to be great helpful for CO2 geological storage studies.
   This paper is proposed against the background of long term and safe storage of CO2 in deep saline aquifers. Experiments for CO2 storage in glass beads bed were inducted at laboratory scale. Quartz beads were filled and packed tightly in the imaging vessel. Gaseous CO2 was then injected into the sample at a constant flow rate and saturated water was driven out. Two CO2 injection directions in the vessel were chose, namely upwards and downwards to observe the effect of buoyancy. Three dimensional scans were carried out using a micro focus X-ray CT system to investigate the distribution of CO2 in sandstone cores.
   Digital cores of those samples were obtained after a series of imaging processing of media filtering, rescaling, and thresholding. Then a maximal ball (MB) algorithm was used to extract the equivalent pore networks. The parameters of the pore networks, such as coordination number, size distributions and shape factors of pore and throat were computed. Gas channeling phenomena was obviously found in water saturated beads bed while CO2 was injected upwards during displacement experiments. A short breakthrough time resulted in low sweep coefficient and only about 10% of saturated water was displaced. Nevertheless, about 80% of saturated water could be driven out and displaced by CO2 while it was injected downwards. Storage capacity of residual trapping was enhanced while CO2 was injected downwards along the beads bed. X-ray micro CT was proved to be an effective technique for the investigation of CO2 storage in core sample and a novel method for the estimation of CO2 storage capacity. (c) 2013 The Authors. Published by Elsevier Ltd.