波谱学杂志

• •    

结合纳米级CT扫描与NMR测井评价低渗砂岩储层渗透率

张朝华1,张伟2*,李勤2,周锐2
  

  1. 1. 中海油田服务股份有限公司油田技术事业部,河北 三河 065201;2. 中海油田服务股份有限公司油田技术事业部深圳作业公司,广东 深圳 518067
  • 收稿日期:2026-02-25 修回日期:2026-04-29 接受日期:2026-05-28
  • 通讯作者: 张伟 E-mail:zhangwei53@cosl.com.cn
  • 基金资助:
    中海油田服务有限公司科技攻关项目(KJ20250300456)

Evaluation of Low Permeability Sandstone Reservoir Permeability Combining Nanoscale CT Scanning and NMR Logging

ZHANG Chaohua1,ZHANG Wei2*,LI Qin2,ZHOU Rui2   

  1. 1. Oilfield Technology Division of China Oilfield Services Limited, Sanhe 065201, China; 2. Shenzhen Operating Company of Oilfield Technology Division of China Oilfield Services Limited, Shenzhen 518067, China
  • Received:2026-02-25 Revised:2026-04-29 Accepted:2026-05-28
  • Contact: ZHANG Wei E-mail:zhangwei53@cosl.com.cn

摘要: 低渗砂岩非均质性强、孔隙结构复杂,采用常规方法难以构建高精度渗透率评价模型.为提升低渗砂岩渗透率评价精度,以南海东部盆地惠州地区文昌组321块岩心为研究对象,开展纳米级电子计算机断层扫描(CT)和核磁共振(NMR)联测实验,明确微米级孔隙度是控制渗透率的关键因素.据此,建立基于微米级孔隙度的低渗砂岩渗透率预测新模型.利用双T2截止值将NMR T2谱划分为纳米级、微米级和亚毫米级三类孔隙组分,实现微米级孔隙度定量计算.实验结果表明:计算的微米级孔隙度与CT实测结果之间的平均相对误差为13.24%,本研究提出模型计算的渗透率与岩心实测渗透率之间的平均相对误差仅为24.07%,远优于传统孔隙度-渗透率关联模型50.27%的误差水平,证实本研究提出模型具有更高的精度和更广泛的适用性.

关键词: 低渗砂岩储层, 数字岩心技术, 核磁共振测井, 渗透率, 微米级孔隙度

Abstract:

Low-permeability sandstones have strong heterogeneity and complex pore structure, making it difficult to construct high-precision permeability evaluation models with conventional methods. To improve evaluation accuracy, 321 core samples from the Wenchang Formation in the Huizhou area, eastern South China Sea Basin, were tested by nanoscale computed tomography (CT) and nuclear magnetic resonance (NMR). Micron-scale porosity was identified as the key factor controlling permeability. A novel permeability prediction model was established based on micron-scale porosity. Using two T2 cutoff values, the NMR T2 spectrum was divided into nanoscale, micron-scale and submillimeter-scale pore components, to realize quantitative calculation of micron-scale porosity. The average relative error between calculated micron-scale porosity and CT measurement is 13.24%. The permeability error of the new model is only 24.07%, much lower than 50.27% of the traditional porosity-permeability model, which proves the new model has higher accuracy and applicability.

Key words: Low-permeability sandstone reservoir, digital core technology, nuclear magnetic resonance (NMR) logging, permeability, micron-scale porosity