基于多目标粒子群算法与TOPSIS的射孔方案优选研究

射孔完井是油气井的主要完井方式之一，在世界范围内得到了广泛的应用。它涉及孔径、孔密、相位、孔深、压实伤害等多种参数，不同的射孔参数对射孔效益有不同的影响，为了能够获得理想的射孔效果，需要对射孔参数进行优化设计。为此，利用多目标粒子群算法(MOPSO)，结合TOPSIS算法对射孔参数进行优化，建立一种射孔方案的优选模型。仿真实验表明该优选模型的有效性，为科学地进行射孔设计、提高油气井产能提供了依据。

Selection of perforation plan based on MOPSO and TOPSIS decision making

Perforation is one of major oil and gas well completion methods. It involves productivity ratio, perforation phase angle, perforation diameter, penetration and etc. Different perforation parameters have different influences on oil-well productivity, in order to obtain ideal perforating effect, the perforation parameter need to be optimized. Perforation scheme mult-attribute decision-making model based on MOPSO and TOPSIS is created in this paper, it aims to provide a scientific guidance for the Perforation. The simulation experimental results show that new models are effective, which offer one kind of science decision-making foundation for petroleum Perforation.