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。
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.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2005年第4期366-369,共4页
Geomatics and Information Science of Wuhan University
基金
国家自然科学基金资助项目(50309013)
关键词
地震特征参数
测井曲线
储层参数
神经网络
专题地图
seismic attribute parameters
well logging curves
reservoir parameters
neural network
thematic map
