چكيده به لاتين
Abstract:
The main goal of this research is well placement and rate optimization in oil production and waterflooding process. For this purpose the streamline simulation model was used and help from streamline model data such as time of flight and the number of streamlines was used to modify the optimization of oil production. Hence, is introduced new objective function for well placement optimization. In this research the presented objective function is three important terms mulitiplication, respectively oil saturation and time of flight are the first two terms of the objective function. Third term is the square of the diffrence between the number of streamlines that are passed from each cell and the number of streamlines that must be passed from that cell to sweep the all of oil volume in that cell. Physically, this function guide more streamlines to the region with high oil saturation and this lead to rduce the time of flight (in other words the oil in the each cell will be sweep at less time). In the following well placement optimization will be do by PSO and GA that both algorithims were appropriate optimum responses. One of the advantage of using the streamline model is remarkable decrease in computational time in compare with other reservoir simulation methods that is clearly seen in this research. the optimization by using of the new objective function shows intelligent movement of the streamline to the high oil saturation cells and it’s the main objective of the presented innovation. In the following, the production rate was optimized . the main problem in the rate ptimization is the Computational Complexity and long calculational time.
In order to reduction in the calculational time a linearization model is expanded and used to optimization process. Using of the linear model reduce the number of run simulator to 0.1 of the nonlinear model.The Production rate optimized by steepest descent method in order to maximize the comulative oil production. in conclusion, observed that change in the start point give diffrente results and that is One of the significant defect of the gradient base algorithm.
Keywords: Oil reservoir, waterflooding, optimization, objective function, streamlines, linearization
