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四川盆地大猫坪构造长兴组测井沉积微相识别
Logging-based sedimentary microfacies identification of Changxing Formation, Damaoping structure, Sichuan Basin
张红英 谢 冰 袁 倩 刘蜀敏 王丽英
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作者单位:中国石油西南油气田公司勘探开发研究院
中文关键字:四川盆地 大猫坪构造 生物礁 沉积微相 测井 模式识别
英文关键字:Sichuan Basin; Damaoping structure; Bioreef; Sedimentary microfacies; Logging, Mode recognition
中文摘要:    川东上二叠统长兴组是四川盆地的主力气层之一,近年来在川东大猫坪长兴组储层天然气勘探取得了较好的进展。大猫坪长兴组气藏主要发育生物礁相储层。为预测生物礁发育的有利相带,开展了测井资料沉积相分析。利用常规测井资料划分岩石类型,由地层倾角、微电阻率扫描成像资料描述生物礁相的形态、岩石结构、礁相组合类型等特征;采用模式识别分析方法,将测井地球物理信息转换成为地质信息,对沉积相进行自动识别。通过对大猫坪长兴组生物礁微相特征描述和刻画,结果表明:①礁相地层沉积模式纵向上划分为礁顶潮坪、礁核、礁间灰泥、礁滩微相,优质储层分布于礁滩相;②基于地质、岩心薄片、测井、试油建立了大猫坪长兴组生物礁微相的测井识别模式;③采用模式识别分析技术识别沉积微相,分析测井曲线对沉积环境的敏感性, 提取反映沉积环境的特征参数,利用特征参数建立沉积微相识别模式。结论认为:模式识别分析技术实现了自动相分析,可以快速识别各类微相,已成功应用于大猫坪长兴组生物礁微相分析中,实钻井应用效果较好。
英文摘要:    Changxing Formation, eastern Sichuan Basin, is one of the principal targets in Sichuan Basin. In recent years, greater progress of natural-gas exploration has been made in Changxing reservoirs, Damaoping structure, eastern Sichuan Basin. Bioreef reservoir rocks are mainly developed in these reservoirs. In order to predict some favorable bioreef development zones, sedimentary facies were analyzed based on logging data. Rock type was divided via conventional logging data, and some features including bioreef-facies
form, rock structure, and bioreef-facies combination type were described by using stratigraphic dip and microresistivity scanning imaging data. Then, some geophysical information of logging was converted into geological one for automatic identifying sedimentary facies by means of model recognition and analysis method. In addition, bioreef-microfacies characteristics of Changxing Formation were analyzed. Results show that (1) for these bioreef-facies strata, the sedimentation mode is vertically divided into four microfacies
of bioreef-top tidal flat, bioreef core, inter-bioreef marl, and bioreef shoal, and most high-quality reservoirs are mainly developed in bioreef shoal microfacies; (2) a logging identification mode is established for these bioreef microfacies of Changxing Formation, Damaoping structure, based on geological description, thin-section identification, and logging and test data; (3) this mode is used to identify sedimentary microfacies, analyze logging curves on sensitive sedimentary environments, and extract characteristic parameters reflecting sedimentary environments further to set up another mode to identify sedimentary microfacies. In conclusion, by virtue of the mode recognition and analysis technology, facies and various microfacies can be automatically analyzed and quickly identified. This technology has already been successfully applied to analyzing the bioreef microfacies of Changxing Formation in Damaoping structure, and obtained better effect in drilling practices.
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国内统一连续出版物号:CN51-1159/TE |国内发行代码: |国际标准出版物号:ISSN1673-3177 |国际发行代码:
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