注水开发油田产油量产水量动态预报的新方法

A New Method of Performance Prediction of Oil and Water Production in Oilfields with Water Injection,

对注水开发油田，提出一种新的产油量、产水量动态预报方法。该方法对油田开发过程的时变性和各种随机干扰因素具有自适应性。文章从信息论角度出发，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，适合于各个阶段的产油量、产水量的动态预报。并且该方法完善了油田产油量、产水量动态预报的理论。最后给出了两个动态预报的实例。

This paper presents a new method of performance prediction of oil and water production in oilfields with water injection. The method is adaptive to various random factors in the process of oilfield exploitation. By using neural network models of nonlinear time series prediction, we constructed neural network predictors for the oil production and water production of oilfields. Prediction results show that the predictors have high accuracy and can be used for prediction of oil and water production in different production periods. This method improves the theory of the performance prediction of oil and water production. Two examples of performance prediction were given in this paper.