›› 2015, Vol. 36 ›› Issue (1): 1-1.doi: 10.7657/XJPG20150102

• 论文 •    

玛北地区砂砾岩储集层控制因素及测井评价方法

王贵文1,孙中春2, 付建伟1,罗兴平2,赵显令1,潘拓2   

  1. (1.中国石油大学 油气资源与探测国家重点实验室,北京 102249;2.中国石油 新疆油田分公司 勘探开发研究院,新疆 克拉玛依 834000)
  • 出版日期:2019-01-01 发布日期:1905-07-11

Control Factors and Logging Evaluation Method for Glutenite Reservoir in Mabei Area, Junggar Basin

WANG Guiwen1, SUN Zhongchun2, FU Jianwei1, LUO Xingping2, ZHAO Xianling1, PAN Tuo2   

  1. (1.State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing 102249, China; 2.Research Institute of Exploration & Development, Xinjiang Oilfield Company, PetroChina, Karamay, Xinjiang 834000, China)
  • Online:2019-01-01 Published:1905-07-11

摘要: 玛北地区扇三角洲沉积广泛发育砂砾岩储集层,砂体类型多,控制因素不清,测井评价困难。在岩心观察的基础上,对不同沉积相控制下的岩石单元组合的岩石学特征进行了研究。综合分析实验数据和试油产能资料表明,岩石类型、分选特征以及胶结类型是控制储集层发育的主要因素, 水下分流河道中的灰色含砾中粗砂岩至水上辫状河道褐色砂砾岩相,物性和储集性能呈逐渐变差趋势。提出了砂砾岩岩性岩相测井表征方法:利用电阻率成像测井资料识别岩石结构构造,进行砂砾岩沉积微相划分;利用常规测井资料和电阻率成像测井资料识别岩性;利用中子—核磁有效孔隙度差值评价泥质含量、分选系数等岩性参数。该综合方法可用于砂砾岩储集层的划分及分类评价。

Abstract: The fan delta deposit in Mabei area of Junggar basin is characterized by wide distribution of glutenite reservoirs, but various types of sand bodies and unclear control factors on the reservoirs caused the difficulty of related logging evaluations. Based on the core samples’ observation, this paper studied the petrology of the core unit combination controlled by different sedimentary facies, and comprehensively analyzed the core lab and the formation test data. The results show that the rock type, sorting feature and rock cementation type are the main control factors on the glutenite reservoir development. The physical property and reservoir quality tend to become poor from the grey pebbly medium-coarse sandstone in underwater distributary channel to the brown glutenit facies in overwater braded river channel. The log characterization method for the glutenite lithology and lithofacies is as follows: a) using FMI logs to identify the rock texture and structure, and classify the microfacies of glutenite; b) using conventional logs combined with FMI logs to identify the lithology, and c) using the difference between neutron log porosity and NMR effective porosity to evaluate the shale content, sorting coefficient, etc. The case study indicates that this combination method can be applied to classification and evaluation of glutenite reservoirs

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