应用表明，RBF神经网络在储层表征问题中有着广阔的应用前景。
The results show that the RBF neural network is very promising for the application of petroleum reservoir characterization.
在利用测井资料进行油藏描述、储层表征的过程中，首先必须对测并资料进行标准化，使测井曲线在研究工区内有统一的刻度。
Geophysical logging data must be first normalized to guarantee a unified scale in research area during the process of reservoir description and reservoir bed characterization.
建立准确的储层参数测井解释模型，是进行储层非均质性表征的前提和基础。
Establishment of accurate logging interpreting models for reservoir parameters is the foundation and premise for characterizing the reservoir heterogeneity.
经过统计分析只有前两段回归直线得到的分数维才能定量表征储层的物性特征和孔隙结构特征。
Through statistical analysis only the former two linear regression can be fractional quantitative characterization of the reservoir characteristics and pore structure characteristics.
利用压汞曲线计算出来的分数维来定量表征储集层微观孔隙结构的非均质性；
The fractal dimension calculated from mercury injection curves is used for quantitative characterization of heterogeneity in micro-porosity structure of reservoir.
储层随机地质建模技术做为油藏三维定量表征的一项新技术，可以定量刻画三维空间油藏地质特征。
The technology of reservoir stochastic geological modeling, which is a new technology describing reservoir three-dimensional feature, can describe three-dimensional space reservoir geological feature.
储层微相研究是油田开发后期储层非均质性精细表征及剩余油分布规律研究的重要内容。
Analysis of oil reservoir microfacies is important for the study of remnant oil and the anisotropy features of oil reservoir in later period.
系统总结了国外近年来利用分形理论定量表征储层非均匀性方面的进展情况。
The paper summarizes how to describe the reservoir heterogeneity quantitatively with fractals in the recent years.
砂岩储层的微观非均质性主要由砂岩孔隙特征、粘土矿物和孔喉分布等表征。
The microheterogeneity in the sand reservoirs is represented by the pore nature, clay mineral composition and pore throat distribution.
砂岩储层的微观非均质性主要由砂岩孔隙特征、粘土矿物和孔喉分布等表征。
The microheterogeneity in the sand reservoirs is represented by the pore nature, clay mineral composition and pore throat distribution.
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