An Injection Rate Optimization in a Water Flooding Case Study with an Adaptive Simulated Annealing Techniques

Abstract

This paper introduces an effective production optimization and a water injection allocation method for oil reservoirs with water injection. In this method, a two-stage adaptive simulated annealing (ASA) is used. A coarse-grid model is made based on average horizon permeability at the beginning iterations of the optimization to search quickly. In the second stage, the fine-grid model is used to provide the accuracy of the final solution. A constrained optimization problem to maximize an objective function based on net present value is implemented. Allocation factors from the streamline simulation are used to help for the appropriate estimation of initial water injection rates. The proposed optimization scheme is used for a field sector simulation model. The results show that the optimized rates confirm the increment of total oil production. Optimized oil production and total water injection rates lead to an increase in the total oil production from 385.983 (initial guess) to 440.656 Msm3. This means a recovery factor increment by 14.16%, while the initial rates were much higher than the optimized rates. Moreover, the recovery factor of optimized production schedule with an optimized total injection rate is 2.20% higher than the initial production schedule with an optimized total water injection rate. The allocation of the water injection rates and the revision of allocation rates result in 446.383 and 450.164 Msm3. The revision of the water rates allocation provides a reduction of water cut during production.

Keywords

• life-cycle optimization
• adaptive simulated annealing
• water flooding
• streamline simulation