摘要
基于取心井薄片鉴定、岩石化学分析等资料, 结合岩心观察结果,对大港枣园油田枣35块火成岩油藏岩石类型进行了划分,研究了不同岩性的测井响应特征;在分析岩性与电性相关关系的基础上,采用多参数交会图法和神经网络法建立了研究区火成岩岩性识别模式,并对区内17 口井进行了岩性识别。岩性识别结果为研究区火成岩精细油藏描述和双重介质储层地质建模奠定了基础;识别方法和技术思路对其它类型火成岩岩性识别与评价具有借鉴意义。
Based on core observation, thin section examination and chemical analysis, igneous rocks in Block Zao 35, Zaoyuan oilfield, are divided into different lithologic types, and the log responses of these types are investigated. By analyzing correlation between lithologic types and their responses, a lithologic identification model has been established using some multi parameter crossplots and a neural network tool, and has been applied to identify lithology of igneous rocks in 17 wells. The results may lay a foundation for refined reservoir descriptions and a geologic modeling of dual porosity reservoir in the study area. This idea and method may also be helpful to evaluation of igneous rocks with other types.
出处
《中国海上油气（工程）》
2005年第1期25-30,共6页
China Offshore Oil and Gas
基金
中国石油天然气股份公司2003-2004年科技攻关项目"火成岩裂缝性稠油油藏储层表征及开发技术研究"部分成果
关键词
火成岩
岩性
识别方法
大港枣园油田
油藏分析
神经网络系统
igneous rock
lithologic identification
log response
multi-parameter crossplot
neural network
reservoir in Block Zao-35
