基于地震-测井数据预测储层参数空间分布规律的神经网络模型

Neural Network Models for Predicating the Spatial Distribution of Reservoir Parameters Based on Seismic and Well Logging Dat

摘要: 研究了地震资料的特征参数与储层参数间的神经网络模型,建立了相互之间的非线性映射,可以横向预测目的层的储层参数,实现地震资料和测井资料联合预测储层参数的空间分布规律。实验结果表明,该方法是可行的。

Abstract: The neural network models have been studied and developed to establish the non-lineal imaging between the seismic attribute parameters and reservoir parameters. The neural network models can be used to predicate reservoir parameters of the targets and realize the integration of seismic and well logging data, in order to predicate the spatial distribution of reservoir parameters. With actual well logging and seismic data from one of fields in our country, the simulation with the neural network models is finished. The results show that this method is feasible, and the corresponding thematic maps are made.