神经网络在辽河滩海地区油气储层产能预测中的应用

从达西二维产量公式出发 ,研究储层产能的理论方程 ,通过相对渗透率与含水饱和度的函数关系为纽带 ,导出油气储层产能与储层有效孔隙度、渗透率以及电阻率之间的多元关系式 ,在此基础上 ,结合测井学的基本理论 ,探讨了利用测井资料进行储层产能预测的基本思想 ,最后采用人工神经网络技术建立了储层产能预测系统 ,该方法用于辽河油田滩海地区海南构造带东营组三段储层的油气产能预测 ,效果良好 ,从而证实了方法的有效性

Application of Neural Network Technology in Oil and Gas Productivity Prediction of the Reservoir in Tanhai Area, Laohe Oilfield

The expression of reservoir productivity was derived from Darcy's two dimensional production formula by means of the relationship between the water saturation of the reservoir and its resistity and permeability. The reservoir productivity is the function of effective porosity, permeability and resistity. The authors discussed the method of predicting reservoir productivity according to log data. The reservoir productivity prediction system was estabilshed by neural network technique. The predicted results of 89.5% in 19 tested wells of Liaohe Oilfield are identical with real testing results. (Xi'an Petroleum Institute, Xi'an, Shaanxi 710065,China)