摘要
含水率是研究生产井生产状况的一个重要参数 ,通常是由Buckely Leverett方程式来确定。但所得到的含水率只能代表某一时刻 ,而含水率是随着油田的开发深入而不断变化。因此在进行井网调整时 ,预测出油田范围内不同位置的含水率非常必要。结合现有井的动、静态资料 ,利用模糊神经网络的方法建立含水率预测模型 ,对任意井位、任意时间的含水率进行预测 。
The water cut is usually determined by the buckely leverett equation, which represent water cut in certain time. with the development of oil field, the water cut varies continuously. so it is necessary to predict the water cut of well on the different location during the different period when the well pattern is adjusted. in this paper, the model of the water cut is set up by using the dynamic and static date of the well that is known by the method of fuzzy neural networks. this model can predict the water cut of the arbitrary well and period.
出处
《西南石油学院学报》
CSCD
2003年第3期30-32,共3页
Journal of Southwest Petroleum Institute
基金
国家"九五"重大科技攻关项目成果部分内容 ( 95- 10 9- 0 1- 0 4 )
关键词
含水率
模糊神经网络
预测
water cut
fuzzy neural networks
prediction
