基于进化算法的油藏水交替注气策略优化

T. P. Ferreira, L. F. Almeida, Juan G. Lazo Lazo
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引用次数: 1

摘要

大多数国家使用石油作为其能源基质的主要来源。提高采收率(EOR)技术的应用越来越广泛,其目的是提高油藏中的油气采收率,提高波及和驱替效率。三次(或高级)采收率技术的使用,如水交替气(WAG)注入,被认为有望达到提高采收率的期望,同时它有助于改变储层的一些化学性质,从而促进其开发。本文介绍了利用进化计算技术对某油藏的水交替注气策略进行优化,以最大化油田的净现值(NPV)。它创建了一个程序,用JAVA开发,通过使用实现的自定义进化算法执行优化,并使用商业软件$\mathbf{GEM}^{\bigcirc\!\!\!\text{R}}$,它执行数值模拟并将重要数据传递给优化器。
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Optimization of the Water Alternating Gas Injection Strategy in an Oil Reservoir Using Evolutionary Algorithms
The majority of the countries use oil as the main source of their energetic matrices. Techniques of Enhanced Oil Recovery (EOR) have been widely used with the aim of increasing oil and gas recovery trapped in oil reservoir, as 011 as improving the sweep and displacement efficiency. The use of tertiary (or advanced) recovery techniques such as Water Alternating Gas (WAG) injection has been considered promising to attend the expectations of improving the oil recovery, at the same it contributes with changes in some chemical properties of the reservoir that facilitate its exploitation. This paper describes the optimization of a water alternating gas injection strategy in an oil reservoir taking into account techniques of Evolutionary Computing used for maximizing the Net Present Value (NPV) of the field in analysis. It was created a program, developed in JAVA, that performs the optimization through the use of the custom evolutionary algorithm implemented and also uses the commercial software $\mathbf{GEM}^{\bigcirc\!\!\!\text{R}}$ , which executes the numerical simulation and deliver important data to the optimizer.
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