混合智能系统在测井储层识别中的应用  

Application of hybrid intelligent system for log reservoir identification

作　　者：程国建[1] 张喜锋[1] 王潇潇[1] 

机构地区：[1]西安石油大学计算机学院,陕西西安710065

出　　处：《电子技术应用》2007年第10期128-130,共3页Application of Electronic Technique

基　　金：国家自然科学基金项目(40572082)

摘　　要：介绍混合智能系统,并充分利用该系统在学习、自动模式识别和近似推理方面的优势,采用模糊神经混合方法对石油测井中的储层进行识别。该方法通过对测井数据的学习,运用模糊逻辑与神经网络相结合的混合系统对测井数据进行提取和优化;根据来自不同油井的观测数据,采用一个两阶段的策略决定预测模型的结构和参数,进而对测井储层进行识别。给出了该混合方法预测的初步结果,为油井的开发提供了重要的参考。The paper mainly present hybrid intelligent system, and makes full use of advantages of the system in learning, automatic pattern identification and approximate reasoning. The approach uses a hybrid system of fuzzy Logic and neural network for extraction and optimization to log data via learning from it. A two-phase learning strategy is adopted to determine the structure and parameters of the predictive model on the basis of experimental data derived from different log, hence a log reservoir is idendified. Preliminary results on the identification of the hybrid approach are reported. The important reference is provided for exploration of a new well.

关 键 词：智能系统 模糊神经 储层识别 神经网络 模糊逻辑 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置]