由地震属性向储层参数转换的综合效果分析

2002年 41卷 第No. 2期
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A comprehensive effect analysis of conversion from seismic attributes to reservoir parameters
石油大学地球资源与信息学院, 山东东营257061
Earth Resources and Information Institute, University of Petroleum, Dongying 257061,China
利用逐步回归分析、神经网络、相关滤波、协克里金和非参数回归分析等方法,实现了由地震属性与测井资料联合应用对孔隙度参数的平面分布预测。通过实例分析,比较了各自的地质效果,归纳总结出各种方法的特点及应用条件.
By means of stepwise regression analysis, neural network, correlation filtering, CoKrige, and nonparametric regression, this article realizes the prediction of porosity distribution from seismic attributes and logging data. The behaviors of different methods and their conditions of application are summarized through the comparison of geological effects resulted from case analysis.
储层参数预测; 多元逐步回归; 神经网络; 相关滤波; 协克里金; 非参数回归;
prediction of reservoir parameter; stepwise multivariate regression; neural network; correlation filtering; Cokrige; nonparametric regression;