人工神经网络技术在储集层参数预测中的应用

建立在传统的经验模型或统计模型基础上的常规测井储集层参数预测方法其精度和成功率均较低。介绍了人工神经网络在处理非线性相关参数预测方面的优势和多层前馈神经网络的结构,以及在处理非线性参数过程中的原理和数学计算方法。通过实例说明了神经网络技术在测井孔隙度参数预测中所取得的成果。

Application of Artificial Neural Networks to Reservoirs Parameters Prediction

The conventional method for prediction of well logging reservoir parameters based on experimental mod-els and statistical models shows lower accuracy and lower successful rate. The artificial neural network is a non-liner dynamic system. It has well prospect in logging interpretation and reservoir parameters prediction. This paper provides a case to illustrate the adv antage of the artificial neural network technique in logging porosity parameters prediction.