Research on KPOD Model Order Reduction Method for Improving Reservoir Simulation Speed

Under the existing calculation conditions, improving reservoir simulation computing speed is of great significance, and it is a hot research issue in the world. At present, the proper orthogonal decomposition (POD) method is widely used to improve reservoir simulation speed, but this method is more sensitive to the input parameters of the system, and reduces the simulation accuracy and efficiency. Krylov enhanced POD (KPOD) method based on Krylov and POD combines the moment matching property of Arnoldi with POD's data generalization ability to alleviate POD's dependence on input conditions. In this paper, the KPOD method is applied to reservoir simulation, our results show that KPOD outperforms POD in the calculation speed and accuracy, and verify the effectiveness and practicality of the method.