摘要： 桂中坳陷柳城北区块下石炭统鹿寨组页岩气取得突破,有望成为四川盆地以外海相页岩气的接替领域。但受地层非均质性及纵横向相变频繁的制约,开展页岩类型识别和储集层评价存在困难。文中建立了基于“矿物组分+TOC含量”的页岩类型划分方案,利用元素—矿物转换最优化方程和BP神经网络模型分别实现页岩成分和TOC含量的测井识别与预测,并采用成像测井动态切片和纽扣电极视电导率图像2种方法识别表征页岩纹层。通过精细刻画不同页岩类型的纹层发育程度和含气性特征,阐明了研究区有利页岩类型及分布特征。研究表明: 鹿寨组一段发育5种典型页岩类型。受沉积古环境控制,页岩分布呈现出较强的纵向非均质性。鹿寨组一段整体处于下斜坡相沉积环境,纵向上①至⑦小层沉积水体逐渐变浅,灰质含量减少而陆源碎屑供给增多,总有机碳含量也逐渐降低,页岩类型由富有机质硅质混合页岩、富有机质黏土质混合页岩逐渐相变为含有机质硅质混合页岩。其中③小层中富有机质硅质混合页岩与富有机质黏土质混合页岩的页岩组合类型有机质丰度高,纹层组合类型及发育程度较优,整体含气量和脆性均较高,为研究区的有利页岩类型。

关键词: 页岩类型, 测井识别, 纹层, BP神经网络, 鹿寨组, 下石炭统, 桂中坳陷

Abstract: The shale gas of Luzhai Formation in Liucheng North block of Guizhong Depression has made a breakthrough and is expected to become a replacement field for marine shale gas outside Sichuan Basin. However,it is difficult to identify shale type and evaluate reservoir due to the formation heterogeneity and frequent transverse and horizontal phase transformation. In this paper,a shale type division scheme based on “mineral composition+TOC content”is established. Logging identification and prediction of shale composition and TOC content are realized by using elite-mineral conversion optimization equation and BP neural network model,respectively. The shale layers are identified and characterized by two methods: image log dynamic slice and button electrode apparent conductivity image. By elaborating the stratification degree and gas bearing characteristics of different lithofacies types,the favorable shale types and distribution characteristics in the study area are described. The results show that five typical shale types are developed in the Member 1 of Luzhai Formation. Controlled by sedimentary palaeoenvironment,the shale distribution in the study area shows strong vertical heterogeneity. The Member 1 of Luzhai Formation is located in the lower slope sedimentary environment as a whole,and the sedimentary water in the vertical layer(①~⑦)gradually becomes shallower,the content of gray matter decreases while the supply of terrigenous debris increases,and the total organic carbon content also gradually decreases. The shale type gradually changes from organic-rich siliceous mixed shale and organic-rich clayey mixed shale to organic-containing siliceous mixed shale. The shale assemblage types of organic-rich siliceous mixed shale and organic-rich clayey mixed shale in small layer ③ has high organic matter abundance,better laminae combination type and development degree,and higher overall gas content and brittleness,which are favorable shale types in the study area.

Key words: shale type, logging identification, laminae, BP neural network, Luzhai Formation, Lower Carboniferous, Guizhong Depression

中图分类号: 

• P631.8