A Stochastic Optimization Approach for Profit Maximization Using Alkaline- Surfactant-Polymer Flooding in Complex Reservoirs

摘要

In heterogeneous reservoir formations, water tends to have early breakthrough due to the overriding and viscous fingering during secondary recovery. The overall hydrocarbon recovery efficiency remains very low in gas and water flooding projects because of less viscosity and higher mobility of water and gas. Therefore, there is an underlying need for improving recovery through a suitable chemical enhanced oil recovery (EOR) method. After investigating the feasibility of alkaline, polymer, surfactant, surfactant-polymer, alkaline-polymer and alkaline-surfactant-polymer (ASP) flood, ASP was selected as a chemical EOR method in low permeability heterogeneous reservoirs. However, the performance of the ASP flooding was highly dependent on operational parameters. Thus, it was important to select these parameters with extensive care to increase the recovery along with the profitability. The relationship between the ASP flooding operational parameters and profitability (NPV) has not been yet understood fully. In this research, the new stochastic optimization approach to optimize the ASP flooding operational parameters has been proposed. To gain the objective of this research, a numerical simulation study was carried out and Particle Swarm Optimization (PSO) was implemented as an optimization algorithm. The net present value (NPV) served as the objective function that has to be maximized among the compared flooding processes. The used operational parameters were location of production and injection well, number of injection cycles, oil production rate, ASP injection time, ASP injection rate, alkaline- surfactant and polymer concentrations, surfactant and polymer viscosities. Sensitivity study of these parameters shows significant impact on net present value and ultimate oil recovery. Results also confirm that NPV is increased significantly after the optimization of all flooding parameters by using Particle Swarm Optimizer. The new optimized model was developed for designing the ASP as a chemical EOR method in low permeability heterogeneous reservoir. It can be served as a handy tool for reservoir engineer to select the best ASP flood parameters to achieve maximum NPV.