Production Optimization of Chemical Flooding Based on Reservoir Engineering Method

Abstract

Production optimization is an important way to improve technical and economic benefits in the process of reservoir development. Generally, most production optimization problems of chemical flooding are solved separately using mathematical algorithms, which limits optimization efficiency. This paper introduces the prior scheme obtained from reservoir engineering method into the optimization mathematical model to improve the efficiency of production optimization problems of chemical flooding. Firstly, the reservoir numerical simulation model and optimization mathematical model for chemical flooding are established. Secondly, the injection and production allocations are carried out through statistical analysis of the present development performance of reservoir, and a prior scheme based on reservoir engineering method is obtained. Finally, the prior scheme is used as the initial scheme for optimization. The optimization mathematical model takes net present value as the objective function, and the injection-production volume and chemical agent concentration as the optimization variables. The solving algorithm adopts particle swarm optimization. It can be seen from the results that the net present value of the uniform scheme is 0.761 × 10⁸ RMB while 0.963 × 10⁸ RMB for the prior scheme, which has an increase of 26.54%. Moreover, the conventional method converges to 1.317 × 10⁸ RMB after 22 iterations, while the proposed method converges to 1.328 × 10⁸ RMB after 11 iterations. The proposed method reduces calculation amount by 50% with satisfactory accuracy. Therefore, the proposed method using the prior scheme obtained from reservoir engineering method as the initial scheme achieves better optimization performance than conventional method. This method achieves the combination of mathematical theory and engineering experience, and providing an effective way to reduce calculation costs and increase efficiency for solving reservoir optimization production problems.

Copyright 2023, IFEDC Organizing Committee.

This paper was prepared for presentation at the 2023 International Field Exploration and Development Conference in Wuhan, China, 20–22 September 2023.

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