摘要
根据常规组合测井、地层倾角测井及成像测井资料的测井相序列特征以及利用神经网络岩相处理结果,对塔中地区志留系沉积相类型及有利沉积相带的空间展布和古水流方向进行了研究。结果表明,将该区潮坪沉积划分为潮下带砂坪、潮间带砂泥坪和潮道、潮上带泥坪4个微相,与其他取心井段(或未取心井段)岩屑录井的对比符合率较高;该区志留系塔塔埃尔塔格组(下砂岩段)主要物源来自西北方向,次要物源来自东北方向。利用常规测井解释的岩性剖面、岩心刻度测井处理解释的沉积学倾角结果(沉积构造和古水流)和神经网络岩相处理解释成果,建立了塔中地区志留系关键井的测井沉积亚、微相解释模型。该模型为工区关键井垂向旋回叠置关系和沉积体系的空间展布特征研究提供了连续的、较准确的岩相剖面,对于海陆过渡相的层序划分对比和在塔里木盆地寻找隐蔽油气藏亦有一定的借鉴作用。
According to the sequence characteristics of well logging sedimentary facies obtained by common logging data,dip logging data and imaging logging data and the litho-facies interpretation by artificial neutral network (ANN), the types, spatial distribution and palcocurrent direction of sedimentary facies in Tazhong area were researched. The results show that detritus tidal flat deposits include sub-tidal sand flat, inter-tidal channel, mixed sand-mud flat, supra-tidal mud flat. The comparison of litho-facies to logging data section shows almost no difference. The provenance is mainly located in the northwest of the study area, and secondary provenance is northeastern during the depositional period of lower sandstone paragraph. Based on litho-logies section interpreted by logging data, the sedimentary structure and palcocurrent interpreted by using dip logging with the core correction and treatment results by ANN, the logging data models and deposition models of the key wells of Silurian sedimentary micro facies in Tazhong area were established. These models not only provide sequential and relatively exact litho-facies section for the analysis of relations of vertical cycles overlay of key wells, but also contribute to the research of spatial distribution of sedimentary system in the study region. In addition, the conclusion is also helpful to sequence division and correlation of transitional continental-oceanic facies and to the search for subtle oil and gas reservoirs in Tarim area.
出处
《中国石油大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2006年第3期40-45,共6页
Journal of China University of Petroleum(Edition of Natural Science)
关键词
塔里木盆地
塔中地区
志留系
测井沉积相
解释模型
Tarim Basin
Tazhong area
Silurian
well logging sedimentary facies
interpretation model