Simulation Run Time Reduction using Model Order Reduction Techniques

Simulation Run Time Reduction using Model Order Reduction Techniques

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Part of #Simulation Run Time Reduction using Model Order Reduction Techniques# :

Publishing year : 2012

Conference : The first international conference on oil, gas, petrochemicals and power plants

Number of pages : 8

Abstract: Optimization and real-time control of production scenarios in oil / gas reservoirs is time consuming and requires powerful computers with a high amount of storage capacity. This is because these systems are of a large scale. The timeconsuming problem of running such models is handled in two ways: Parallel Computing andModel Simplification. Model simplification is implemented in two ways by Black Box Modeling and White Box Modeling. [1]. Recently, Model Order Reduction (MOR) techniques are proposed which benefit from strong points of the so-called white-box and blackbox's traditional modeling approaches. Since the governing equations of the multi-phase fluid flow in the reservoir are mostly nonlinear; Therefore, nonlinear model order reduction methods likeProper Orthogonal Decomposition (POD) are used to reduce the system order and accelerate the simulation process. As reported in the literature, MOR by POD has resulted in a speeding factor of 3-4 when applied to the system Of equation solved by Newtonmethod. By applying the Newton method, it would not be possible to achieve higher speeding factors since the full order Jacobian matrix should be computed in every iteration to obtain a reduced Jacobian matrix (Jr) [2]. In this work, the POD is applied to a system of equations which is solved by the IMPES method and is encouraged by a speeding factor of 6 or more.