应用CT成像技术研究岩心孔隙度分布特征

高建; 吕静

应用CT成像技术研究岩心孔隙度分布特征

高建¹,
吕静²

1. 中国石油勘探开发研究院石油采收率研究所, 北京 100083;
2. 中国石油勘探开发研究院采油工程研究所, 北京 100083

基金项目:

中国石油天然气股份有限公司资助项目(2008A-1402)

详细信息

作者简介:
高建(1974-),男,2007年获中国石油大学(北京)油气田开发工程专业博士学位,现为中国石油勘探开发研究院博士后,主要从事油层物理与渗流力学研究,Tel:010-62093020,E-mail:gaojianeor@petrochina.com.cn

中图分类号: TE311
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出版历程
- 收稿日期: 2009-02-08
- 网络出版日期: 2022-12-14

Study of Porosity Distribution Features Using X-Ray CT

GAO Jian¹,
LÜ Jing²

1. Enhanced Oil Recovery Department, Research Institute of Petroleum Exploration & Development, Petro China, Beijing 100083, China;
2. Partment of Production Technology, Research Institute of Petroleum Exploration & Development, Petro China, Beijing 100083, China

摘要

摘要: 清楚地识别岩心内部孔隙度分布特征,并对其进行定量描述,有助于深入研究岩心的渗流特性。应用CT成像技术,通过对干岩心和饱和地层水岩心扫描,重建了岩心不同扫描层面、沿某正交切面以及三维孔隙度分布图。应用孔隙度频率分布和累积频率分布曲线得到了岩心孔隙度分布的统计特征。将岩心孔隙度划分为“层面级”和“岩心级”两个级别,选用7种参数对岩心孔隙度分布的集中趋势、离散程度和分布形态进行表征。研究实例表明,同一岩心不同扫描层面孔隙度分布存在明显差异,其集中程度、离散程度和分布形态均有所不同。采用这7种表征参数可精细刻画岩心孔隙度分布特征。
- CT成像 /
- 岩心 /
- 孔隙度分布 /
- 表征方法
Abstract: Recognizing core's porosity distribution feature clearly and characterizing it quantitatively is very important when studying core sample's seepage feature.By scanning dry core and the core saturated with formation water, the porosity distribution features of each scanning slice and the whole core were obtained, and the porosity distribution images of each slice, orthogonal and three dimensional were reconstructed.Statistical features of core porosity distribution could be derived from frequency distribution and cumulative frequency distribution curves of porosity.The level for studying porosity distribution features of core were divided into two levels, 'slice level' and 'core level'.Seven parameters were selected to characterize the central tendency, dispersion and distributional patterns of porosity distribution.It's showed that, the porosity distribution of different scanning slices varied a lot, and core's porosity distribution feature could be characterized well by using the seven parameters.
- CT scanning image /
- core /
- porosity distribution /
- characterization method