报告题目：Reduced-Order and Multiscale Modeling Approaches for Geological CO2 Storage

　　报 告 人：Dr. Bo Guo

　　单 位：Department of Energy Resources Engineering, Stanford University

　　时 间：2016年12月29下午4:00-5:00

　　地 点：大气所40号楼319会议室

　　Carbon capture and storage (CCS) has been identified as the only technology that can significantly reduce anthropogenicCO2 emissions while allowing continued use of fossil fuels. CCS involves permanent storage of the captured CO2 into deep geological formations, leading to a flow system of two fluid phases (injected CO2 and displaced resident salt water) that requires modeling tools to simulate injection and migration of both fluids. While high-fidelity full three-dimensional (3D) multiphase flow models are available, their application for practical analysis is challenging due to their high computational costs and the huge uncertainty of subsurface geological data.

　　In this seminar, I will introduce two alternative computationally efficient modeling approaches: reduced-order and multiscale models. The reduced-order model assumes vertical pressure equilibrium (due to strong buoyancy of CO2) and a macroscopic sharp interface between CO2 and salt water, which simplify the 3D two-phase flow system into a 1D nonlinear advection-diffusion equation. Such simplifications allow us to solve the system analytically and perform detailed analysis of fluid flow behaviors and CO2storage efficiency, as well as leakage risk assessment. In the second approach, we develop a multiscale model that maintains computational efficiency while relaxing the vertical equilibrium assumption. Algorithms of this type fit naturally into a multi-scale framework, and are able to produce similar results compared to full 3D models for both homogeneous and heterogeneous aquifers. Overall, the two new modeling approaches allow fast simulation, risk assessment, and uncertainty quantification for CO2 injection and migration in the subsurface.