松南深层火山岩CO_2气层测井特征与含量预测  

LOGGING IDENTIFICATION AND CONTENT PREDICTION OF CO_2 BEARING RESERVOIRS IN DEEP VOLCANIC IN SOUTH SONGLIAO BASIN

作　　者：郭宇航[1] 潘保芝[1] 

机构地区：[1]吉林大学地球探测科学与技术学院

出　　处：《国外测井技术》2012年第6期24-27,3,共4页World Well Logging Technology

摘　　要：本文针对火山岩内的CO2气层,研究区域定在松辽盆地南部,火山岩是松辽盆地CO2气层的重要储集层,而一般的识别和含量预测方法不能取得很好的效果,从测井资料着手进行CO2气层测井识别与含量预测,选取5种常用的测井数据(GR,RT,CNL,DEN,AC),在已知井段进行识别运用主成分分析和最小距离判别法,可以得到很好地识别效果,之后采用BP神经网络进行含量预测,得到结果与试气结论比较,取得较好效果。This article is about the CO2-bearing reservoirs in igneous rocks.The selected area lies in the south part of Songliao basin.Igneous rock is an important reservoir of CO2 gas here.General recognition and content prediction methods can not get good results so that we deal with the problem from logging data.We select 5 kinds of conventional logging parameters (GR,RT,CNL,DEN,AC).Principal component analysis and minimum distance discrimination methods are used to identify the known hole section which achieved good result.Then BP neural network is used to predict the content.The results are compared with that of gas testing conclusion.It shows that the method is effective.

关 键 词：松辽盆地 CO2气层 测井识别 含量预测 测井 

分 类 号：TE37[石油与天然气工程—油气田开发工程]