新疆石油地质 ›› 2021, Vol. 42 ›› Issue (1): 107-112.doi: 10.7657/XJPG20210115

• 应用技术 • 上一篇    下一篇

碳酸盐岩孔隙-裂缝双重网络模型构建及分析

罗瑜1, 王寅2, 王容1, 袁雯2   

  1. 1. 中国石油 西南油气田分公司 勘探开发研究院,成都 610093
    2. 科吉思石油技术咨询有限公司,北京 100176
  • 收稿日期:2020-04-03 修回日期:2020-06-18 出版日期:2021-02-01 发布日期:2021-02-24
  • 作者简介:罗瑜(1982-),男,重庆人,工程师,硕士,储层评价,(Tel)13880713587(E-mail) Luo_yu@petrochina.com.cn
  • 基金资助:
    国家科技重大专项(2016ZX05052)

Construction and Analysis of Pore-Fracture Network Model of Carbonate Rock

LUO Yu1, WANG Yin2, WANG Rong1, YUAN Wen2   

  1. 1. Research Institute of Exploration & Development, PetroChina Southwest Oil & Gasfield Company, Chengdu 610093, China
    2. Colchis Petro-Consulting Ltd., Beijing 100176, China
  • Received:2020-04-03 Revised:2020-06-18 Online:2021-02-01 Published:2021-02-24

摘要:

为了明确孔隙-裂缝型碳酸盐岩微观渗流机理,需构建能够精准表征真实孔隙-裂缝双重介质系统三维结构的数字化模型。利用碳酸盐岩样品CT扫描图像和图像分割技术,构建出反映样品结构的孔隙-裂缝双重介质数字岩心模型,并依据不同的形态特征参数,分离出样品的孔隙和裂缝空间。通过中心线提取法和最大球填充法,对碳酸盐岩裂缝空间进行了裂缝网络模型提取,结合碳酸盐岩孔隙网络模型,融合为一套孔隙-裂缝双重网络模型,该模型计算得出的孔隙度和绝对渗透率与常规物性实验所获数据较为接近。基于该方法构建的碳酸盐岩孔隙-裂缝双重网络模型能够精准表征孔隙-裂缝双重介质系统的真实三维结构,可用于后期微观渗流机理的深化研究。

关键词: 碳酸盐岩, 双重介质, CT扫描, 图像分割, 数字岩心模型, 孔隙网络模型, 裂缝网络模型

Abstract:

In order to study the microscopic flow mechanism of dual-porosity carbonate rock which contains both pore and fracture, a dual-porosity model should be built which can accurately characterize the pore-fracture system. We first constructed a digital rock model with a real pore-fracture system based on CT images and image segmentation technique before separating the fractures from the pores. Then centerline extraction and maximal ball methods were applied to construct a fracture network model and merge it with a pore network model into a pore-fracture network model. The porosity and absolute permeability calculated on the pore-fracture network model shows good agreement with the results from conventional property experiments. The pore-fracture network model can accurately characterize the real pore-fracture system of dual-porosity carbonate rock, and can be used to study microscopic flow mechanism.

Key words: carbonate dual-porosity media, CT imaging, image segmentation, digital rock model, pore network model, fracture network model

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