摘要
对注水开发油田 ,提出一种新的油田动态研究模型 ,即油田产油量、产水量多维时间序列神经网络预测器。同时考虑油田增产措施和油田开发过程时变性 ,对各种随机干扰因素具有自适应性。从信息论角度出发 ,利用神经网络非线性时间序列预测模型 ,构造了油田产油量、产水量的多维时间序列神经网络预测器。结果表明 ,该预测器具有较高的预测精度 ,适合于油田各个阶段的产油量、产水量的动态预报。完善了油田产油量、产水量动态预报理论。
A new dynamic research model for injection water oil fields was presented. The model contains increase production measures and it is adaptive to various random factors together in the process of oil field exploitation. In this paper, using neuron network models of nonlinear multidimensional time series prediction, neuron network predictors for the oil production and water production of oil fields were constructed. Results illustrated that the predictors were up to higher prediction precision. But this method improved the theory of the dynamic prediction of oil production and water production .Finally, an example of the dynamic prediction were given.
出处
《西南石油学院学报》
CSCD
2003年第3期33-35,共3页
Journal of Southwest Petroleum Institute
基金
"油气藏地质及开发工程"国家重点实验室项目 (PLN972 4 )
关键词
油田动态
产量预测
时间序列
神经网络
oil field dynamic research
production prediction
time series
nerve network
