Research On Production Optimization Method Of Intelligent Completion

Intelligent completion in solving the horizontal well water profile control and multi-layer production and other issues,has a strong advantage andgets increasingly field managers' attention,but the technology after years of development has not been large-scale application,the main reason is how to adjust the downhole control valve to achieve the greatest economic benefits of the oil field,that is how to develop a simple,universal and efficient adjustment method of underground control valve.In view of the above problems,this paper analyzes the domestic and foreign research on the basis of a detailed analysis of the various optimal control program to improve the production of intelligent wells and the overall control of the role of the reservoir.In the first place,the passive control strategy is proposed to control the water content of the underground water as the feedback control condition.At the same time,the parameters in the adjust formula of the control valve area are optimized for different reservoir models,which not only improve the production of intelligent completion,but also be used in different oil fields.Secondly,it is assumed that the reservoir model has good predictability in the later stage of oilfield development.On this basis,the numerical model is used as the optimization carrier to study the adaptability of different optimization algorithms in the active control strategy.Finally,by bringing Kalman filter reference into the real-time fitting problem of the reservoir,combined with the optimal control,the structure of the intelligent algorithm is used in the process of optimization.Real-time closed-loop optimization of completion.In this paper,through the Eclipse to build intelligent completion of the numerical model,the use of MATLAB programming algorithm to achieve the reservoir numerical simulation and optimization algorithm combined.After simulating,no matter what optimized production method,the overall benefits of intelligent completion are greater than the traditional way of completion,cumulative oil production and cumulative net present value growth of at least 5%,cumulative water production decreased by about 8%,And in the process of comparing the optimization algorithms,the sequential quadratic programming optimization algorithm shows a faster convergence rate,which provides a reference for the optimization of large-scale reservoir production.It is hoped that this study will provide a powerful method for the optimization of production methods for intelligent completion help.