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Effects of the errors between core heterogeneity and the simplified models on numerical modeling of CO2/water core flooding
Indexed by:Journal Papers
Date of Publication:2020-03-01
Journal:INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
Included Journals:EI、SCIE
Volume:149
ISSN No.:0017-9310
Key Words:CO2 geological sequestration; Numerical modeling/simulation; Multiphase flow; Local trapping; petrophysical heterogeneity
Abstract:Core heterogeneity is an important factor influencing CO2 and brine migration in porous media but difficult to be accurately described using models. In this study, we quantitatively evaluate the effects of the errors between core heterogeneity and the simplified models on numerical modeling of CO2 core flooding. Results indicate: 1) The model error from the 1D simplification of 3D petrophysical heterogeneity could make the multiphase flow modeling fail to reflect the mean behavior of the core plug, and the resultant deviations in the averaged CO2 saturation (S-CO2) can span from -0.1 to 0.2. Besides, using the 1D heterogeneous core model in the modeling generally conceals the local S-CO2 buildup and accordingly clouds judgment about variation trend of the local S-CO2. 2) The settings of the local petrophysical properties for the low-porosity heterogeneous structures in the cores have a significant impact on the predicted S-CO2 distribution in front of these structures. Particularly, the errors in their capillary entry pressure could lead to the significant underestimation of the local S-CO2 near them. Consequently, the model outputs cannot reflect the local S-CO2 buildup behavior. 3) Both magnitude and variation trend of the predicted local S-CO2 could be numerically sensitive to 3D heterogeneity distribution, notably increasing the probability of the mismatching between model predictions and experimental observations. Comparatively, more efforts should be paid to the parameter setting of the heterogeneous structures in order to improve the reliability of the CO2 core flooding modeling. (C) 2019 Elsevier Ltd. All rights reserved.