ABSTRACT Polymer injection, as a prevalent enhanced oil recovery technique in the oil and gas industry, involves injecting water mixed with high molecular weight polymers into the reservoir to enhance oil production. In this paper, we propose the black oil model with polymer injection, which aims to provide a more realistic simulation of multiphase flow in reservoirs by accounting for the complexities introduced by polymer injection. This multi‐physics coupled reservoir model is an extension of the traditional black oil model, which is commonly used in reservoir engineering to simulate the multiphase flow of oil, gas, and water in porous media. The addition of polymer injection introduces complexities related to adsorption onto reservoir rock, changes in permeability and porosity, and non‐Newtonian fluid behavior. To facilitate large‐scale simulation, we present the augmented Lagrangian active set algorithm implemented on a parallel computing framework to solve the resultant nonlinear system of equations, which arises from the finite volume discretization of the governing equations on unstructured grids. Nonlinear strategies, including the variational inequality formulation, the Newton–Krylov subspace solver, and the backtracking globalization technique, are introduced to handle the high nonlinearity of the flow problem. Furthermore, a domain decomposition‐based linear preconditioner is developed to enhance the efficiency and scalability of the proposed Newton‐type active set algorithm. High‐resolution reservoir simulation results are obtained and analyzed for benchmark projects as well as realistic reservoir problems on unstructured grids. The parallel performance of the algorithm is studied on a supercomputer, demonstrating scalability to tens of thousands of processor cores.
Jiang et al. (Thu,) studied this question.