神经网络在油藏描述关键井研究中的应用  

Application of Neural Network in Key Wells for Reservoir Description

作　　者：肖慈珣[1] 罗继红[1] 蔡永香[1] 

机构地区：[1]成都地质学院

出　　处：《测井技术》1993年第1期36-41,53,共7页Well Logging Technology

基　　金：国家自然科学基金委员会;石油天然气总公司和大庆石油管理局联合资助项目的研究内容之一

摘　　要：近年来神经网络在国际上迅速发展并已广泛应用于油气勘探领域,并用于关键井的测井研究之中。通过实际资料的处理解释,建立了两种主要地层参数(孔隙度和渗透率)的模型,其精度及实际预测效果均令人满意。介绍了这项技术的基本特点、实现过程和应用实例。In recent years, Neural Network has been developed and widely used in oil-gas explorations, especially in the study of key wells. Models for two main formation parameters (porosity &. permeability) have been set up through data processing and interpretation, their accuracy and predicted results are satisfactory. The basic features of application of neural network to reservoir description, its implementation process and field examples are also presented.

关 键 词：测井 油藏描述 关键井 神经网络 

分 类 号：P631.84[天文地球—地质矿产勘探]