A computational workflow to study CO2 transport in porous media with irregular grains: Coupling a Fourier series-based approach and CFD

Journal of Cleaner Production(2023)

引用 1|浏览6
Understanding CO2 transport in porous media is important for enhanced oil recovery and CO2 sequestration. In this study, we aimed to develop a computational workflow to automatically simulate CO2 transport in porous media, including generating digital porous media from a grain morphological perspective, a pipeline, and pore-scale modeling. A method for generating porous media using a Fourier series-based approach was proposed for this workflow. Contact detection introduced the Floyd-Warshall algorithm to improve the computational efficiency and application scope of the method. Furthermore, the simultaneous application of parametric equations and grid mapping makes the output results diverse. A pipeline was built to link the proposed method with pore-scale modeling to automate the workflow. Drawing on the developed computational workflow, we simulated CO2 transport in porous media and discussed the effects of varying the different pore structures, capillary numbers and wettabilities. In different pore structures, the dual-porosity model is easily broken through by CO2 causing a small swept area making its oil recovery lower than the single-porosity model. In the capillary number, the CO2-free oil recovery period decreased with an increasing capillary number in the media. The concomitant imbibition in the low capillary number increased swept area and oil recovery but can lead to economic and time losses. At the wettabilities, the maximum recovery was achieved with weak CO2 wetting. This computational workflow can be used as an effective tool to investigate CO2 transport within porous media, contributing to the design and application of innovative enhanced CO2 sequestration and oil recovery method.
Computational workflow, Pore-scale modeling, Multiphase flow, Grain random generation, Fourier series
AI 理解论文