Abstract
The closed-loop reservoir management technique enables a dynamic and real-time optimal production schedule under the existing reservoir conditions to be achieved by adjusting the injection and production strategies. This is one of the most effective ways to exploit limited oil reserves more economically and efficiently. There are two steps in closed-loop reservoir management: automatic history matching and reservoir production optimization. Both of the steps are large-scale complicated optimization problems. This paper gives a general review of the two basic techniques in closed-loop reservoir management; summarizes the applications of gradient-based algorithms, gradient-free algorithms, and artificial intelligence algorithms; analyzes the characteristics and application conditions of these optimization methods; and finally discusses the emphases and directions of future research on both automatic history matching and reservoir production optimization.
Highlights
With the rapid development of the world economy, the depletion of oil resources increases year by year
This paper gives a general review of the two basic techniques in closed-loop reservoir management; summarizes the applications of gradient-based algorithms, gradient-free algorithms, and artificial intelligence algorithms; analyzes the characteristics and application conditions of these optimization methods; and discusses the emphases and directions of future research on both automatic history matching and reservoir production optimization
According to the techniques for determining search direction and step size, the optimization methods can be classified into three categories: gradient-based algorithms, gradient-free algorithms, and artificial intelligence algorithms
Summary
With the rapid development of the world economy, the depletion of oil resources increases year by year. The demand for exploiting the limited oil reserves efficiently and economically becomes increasingly significant and has attracted more global attention in recent years To achieve this goal, an important technique proposed is closed-loop reservoir management. The main idea is to exploit the oil reserves as near to the desired optimum as possible Both automatic history matching and reservoir production optimization are optimization problems as mentioned by researchers such as Brouwer and Jansen (2004), Sarma et al (2005) and Wang et al (2009). The origin of solving reservoir production problems using optimization theories can be traced back to Lee and Aronofsky (1958) They used a linear programming method to maximize the net present value of production for a homogeneous reservoir.
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