石油物探2024，Vol.63Issue(4)：881-889,9.DOI:10.12431/issn.1000-1441.2024.63.04.016
基于岩心渗流能力约束的砂砾岩储层分类方法研究
Classification method for glutenite reservoirs based on core seepage capacity constraints
摘要
Abstract
E3d3(the third member of the Dongying Formation)in oilfield C,Bohai Sea area consists of near-source fan-delta gluten-ite-bearing deposits with high heterogeneity.Continuous reservoir classification results are important for development planning and reservoir stimulation.The lack of log data and single-layer test or production data in offshore oil fields makes it difficult to classify heterogeneous glutenite reservoirs.We combine the advantages of the seepage capacity method and chart method for reservoir clas-sification.Firstly,reservoir classification is performed in terms of seepage capacity based on the analysis of the petrophysical prop-erties of different types of glutenite cores.Then,sensitive log curves are selected to construct reservoir elements and seepage ele-ments and establish reservoir indicators.Finally,core-based seepage capacity classification results are used to constrain reservoir in-dicators,and reservoir classification standards based on the log curves are established.The results of application to oilfield C in Bo-hai Sea area agree well with core-based classification as well as NMR-indicated pore structure and production log data.This study solves the problem of insufficient testing and production data for reservoir classification in offshore oil fields.Continuous vertical and horizontal classification of glutenite reservoirs provides technical support to efficient development of offshore oil fields.关键词
储层分类/测井/砂砾岩/岩心/渗流能力/劳伦茨曲线/储层指示因子Key words
reservoir classification/well Logging/glutenite/core/seepage capacity/Lorentz curve/reservoir indicator分类
天文与地球科学引用本文复制引用
熊镭,王培春,李瑞娟,郑炀..基于岩心渗流能力约束的砂砾岩储层分类方法研究[J].石油物探,2024,63(4):881-889,9.基金项目
国家科技重大专项(2017ZX05032-003)与中海石油(中国)有限公司重大科技专项"渤海油田稳产3000万吨,上产4000万吨关键技术研究"(CNOOC-KJ 135 ZDXM 36 TJ01TJ-GD 2020-02)共同资助.This research is financially supported by the National Science and Technology Major Project(Grant No.2017ZX05032-003)and the Major Science and Technology Project of CN OOC(China)Limited(Grant No.CNOOC-KJ 135 ZDXM 36 TJ01TJ-GD 2020-02). （2017ZX05032-003）
