湖相碳酸盐岩测井岩相识别技术与应用——以柴达木盆地英西地区为例  

Application of logging lithofacies identification technology of lacustrine carbonate rocks:a case study of Yingxi area,Qaidam Basin

作　　者：田明智 朱超 李森明 夏志远 宋光永 王艳清 宫清顺 李亚锋[2] 刘占国 Tian Mingzhi;Zhu Chao;Li Senming;Xia Zhiyuan;Song Guangyong;Wang Yanqing;Gong Qingshun;Li Yafeng;Liu Zhanguo(PetroChina Hangzhou Research Institute of Geology;PetroChina Qinghai Oilfield Company)

机构地区：[1]中国石油杭州地质研究院,310023 [2]中国石油青海油田公司

出　　处：《中国石油勘探》2023年第1期135-143,共9页China Petroleum Exploration

基　　金：中国石油天然气股份有限公司“十四五”前瞻性项目“柴达木盆地页岩油勘探开发理论与关键技术研究”(2021DJ1808);“多类型储集体发育机制与储集能力定量评价技术研究”(2021DJ0402)。

摘　　要：我国湖相碳酸盐岩储层分布广泛,具有极大的油气勘探前景。但该类储层陆源碎屑含量高、岩相种类多,导致岩相识别困难且严重制约了该领域勘探拓展和高效开发,这在埋藏深度普遍大于4000m的柴达木盆地英西地区古近系下干柴沟组上段(E_(3)^(2))尤为典型。以英西地区为例,充分利用区内大量岩心、薄片和实验分析资料,系统分析湖相碳酸盐岩岩相特征及测井响应特征,并建立了识别方法和图版。分析结果表明,英西地区E_(3)^(2)发育颗粒灰云岩、泥晶灰云岩、纹层状灰云岩、泥质膏岩和灰云质泥岩等5种类型的岩相。基于测井响应特征分析,确定自然伽马、骨架密度、体积密度为岩相识别敏感参数,进而首次提出岩石结构因子(RFF)技术;利用计算得到的RFF参数,结合元素测井资料建立了岩相识别图版,将其应用于研究区48口井,在12口取心井中岩相解释平均符合率达到80.2%,应用效果较好。岩石结构因子技术提高了湖相碳酸盐岩岩相识别符合率,对研究储层分布规律、指导勘探开发具重要意义。In China,lacustrine carbonate rocks are widely distributed and show great prospects for petroleum exploration.The high-content terrigenous debris and diversified lithofacies lead to great difficulty in identifying lithofacies and severely restrict the exploration expansion and efficient development in this field,which is typically represented by the upper part of the Paleogene Lower Ganchaigou Formation(E_(3)^(2))in Yingxi area in Qaidam Basin with a burial depth of greater than 4000 m.Therefore,a large number of core data,thin section and experimental analysis data in Yingxi area are studied in detail,and lithofacies and logging response characteristics of lacustrine carbonate rocks are systematically analyzed to establish the lithofacies identification method and chart.The study results show that five types of lithofacies are identified in E_(3)^(2) in Yingxi area,including granular lime-dolostone,micrite lime-dolostone,laminated lime-dolostone,argillaceous gypsum and lime-dolomitic mudstone.The analysis of logging response characteristics indicates that GR,matrix density and bulk density are sensitive parameters for lithofacies identification,and rock fabric factor(RFF)technology is proposed for the first time.The calculated RFF and element logging data are integrated to establish the lithofacies identification chart,which is applied to 48 wells in the study area.The average coincidence rate of lithofacies interpretation reaches up to 80.2%in 12 coring wells,showing good application results.RFF technology supports to improve the lithofacies identification accuracy of lacustrine carbonate rocks,and is of great significance to determine the reservoir distribution law and guide the petroleum exploration and development in practice.

关 键 词：柴达木盆地 湖相碳酸盐岩 岩相识别 测井评价 

分 类 号：P631.8[天文地球—地质矿产勘探]