DOWNLOAD PRESENTATIONWATCH VIDEOIntroduction
The miscible displacement problem models the displacement of the mixture of two miscible fluids in porous media. The problem models an important process in enhanced oil recovery.
Our high order discretization based on Discontinuous Galerkin (DG) method for both Darcy flow and fluid transport is mass-conservative and provides high fidelity simulation results for the miscible flooding even under highly heterogeneous, anisotropic permeability and severe grid distortion.
The DG discretizations result in larger and more ill-conditioned linear systems than the ones from commonly used lower order methods. To address this issue, we apply algebraic multigrid (AMG) and domain decomposition (DD) to construct parallel preconditioners.
With carefully designed Distributed and Unified Numerics Environment (DUNE), we are able to achieve scalability and efficiency for our miscible flow simulator.
Scalable Solver and Preconditioner
We use preconditioned Kylov subspace iterative method as our solver.
The transport system can be preconditioned by overlapping domain decomposition with SSOR or ILU preconditioners.
The Darcy system is preconditioned using overlapping domain decomposition and aggregated algebraic multigrid (AMG) method.The preconditioners yield good convergence even for problem with largely varying permeability in magnitude from 10^{-10} to 10^{-18} m^2 such as in the SPE10 model.
The solvers and preconditioners are scalable on massively parallel computing architecture as we will illustrate in our result where the pressure and concentration are approximated by piecewise quadratic elements over 1,122,000 cells with up to 512 processes on IBM iDataPlex cluster. The AMG solver which is the most time consuming aspect of the simulation is strongly scalable as we will also demonstrate.
