首页 | 本学科首页   官方微博 | 高级检索  
     检索      

交会图和BP神经网络技术在碎屑岩识别中的应用
引用本文:国景星,彭雪还,李飞.交会图和BP神经网络技术在碎屑岩识别中的应用[J].甘肃科学学报,2016(6):13-17.
作者姓名:国景星  彭雪还  李飞
作者单位:1. 中国石油大学 华东 地球科学与技术学院,山东 青岛,266580;2. 塔里木油田勘探开发研究院,新疆 库尔勒,841000
基金项目:华北油田2011年校企合作科研项目“留西留北构造带上第三系油藏沉积相研究”(HBYT-CY3-2011-JS-345).
摘    要:饶阳凹陷新近系馆陶组岩性以碎屑岩为主,岩性复杂多样,单纯利用测井曲线难以对岩性进行较好地识别,对后续测井解释的结果造成了不利的影响。针对该问题,以测井资料为基础,提出了一种首先利用交会图技术将各类岩性进行归纳总结,然后应用BP神经网络技术对归纳后的岩性进行快速识别的方法。从此种方法在留西地区的应用效果来看,该方法对样本数据库中各类岩性的识别精度达到了90%以上,其中泥岩和粉砂岩的识别精度更是达到了100%,大大提高了单纯利用测井曲线对岩性进行分类识别的精度,在油气勘探开发过程中能够发挥较为重要的作用。

关 键 词:交会图  BP神经网络  岩性识别  碎屑岩

Application of Crossplot and BP Neural Network Technique in the Identification of Clastic Rock
Abstract:The lithology of Raoyang depression Neogene Guantao group mainly is clastic rocks,the lithol-ogic characteristic is complicated and varied of which better identification is hard to be achieved only using the logging curve,it has unfavorable influence on subsequent well logging interpretation.Targeting at this problem and based on the logging data to propose a method which first using the crossplot technique to generalize and summarize all kinds of lithologies and then using the BP neural network technique to quick i-dentify the generalized lithologies.According to the application effect of this method in Liuxi area,the iden-tification precision of all kinds of lithologies in the sample data base has reached over 90% and the identifi-cation precision of mudstone and siltstone have even reached 100%,it greatly improve the classification and identification precision of all kinds of lithologies only using the logging curve,it has more importantly in-fluence in the oil and gas exploration and development process.
Keywords:Crossplot  BP neural network  Lithology identification  Clastic rocks
本文献已被 CNKI 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号