地学前缘 ›› 2019, Vol. 26 ›› Issue (3): 140-146.DOI: 10.13745/j.esf.sf.2019.4.22

• 地下空间开发专题研究 • 上一篇    下一篇

地下空间逾渗与裂缝属性的关系分析

董少群，王涛，曾联波，刘凯，梁锋，尹启航，曹东升   

  1. 1. 中国石油大学(北京) 理学院, 北京 102249
    2. 中国石油大学(北京) 地球科学学院, 北京 102249
    3. 中国地质科学院, 北京 100037
    4. 中国地质科学院 深部探测中心, 北京 100037
  • 收稿日期:2019-01-30 修回日期:2019-03-15 出版日期:2019-05-25 发布日期:2019-05-25
  • 通讯作者: 王涛(1987—)，男，博士，助理研究员，主要从事地下空间及油藏描述等方面的综合研究。
  • 作者简介:董少群(1988—)，男，博士研究生，地质资源与地质工程专业，主要从事裂缝建模、裂缝预测及油藏描述的研究。
  • 基金资助:
    中国地质调查局地质调查项目(DD20190287)；中国地质科学院基本科研业务费项目(JYYWF20180301，JKY201903)；国家科技重大专项(2017ZX05013004)

Analysis of relationship between underground space percolation and fracture properties

DONG Shaoqun,WANG Tao,ZENG Lianbo,LIU Kai,LIANG Feng, YIN Qihang,CAO Dongsheng   

  1. 1. College of Sciences, China University of Petroleum(Beijing), Beijing 102249, China
    2. College of Geosciences, China University of Petroleum(Beijing), Beijing 102249, China
    3. Chinese Academy of Geological Sciences, Beijing 100037, China
    4. SinoProbe Center, Chinese Academy of Geological Sciences, Beijing 100037, China
  • Received:2019-01-30 Revised:2019-03-15 Online:2019-05-25 Published:2019-05-25
  • Supported by:
     

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摘要： 裂缝连通性评价是地下空间研究的重要内容。逾渗分析是研究裂缝网络连通性的一种有效手段。裂缝网络逾渗临界值多使用裂缝间接表征参数(如分形维数)来确定，但存在裂缝网络连通性不同却有相同间接表征参数的情况,这降低了预测的可靠性。为避免此类问题并更加准确快速地表征裂缝网络的连通性，文章在构建逾渗临界值方程时，摒弃了间接参数简化的方式，使用裂缝直接表征参数(如裂缝数量、长度等)进行非线性拟合。通过二维数值模拟建立不同参数的离散裂缝网络模型，分析逾渗低、中、高概率临界条件与裂缝直接表征参数的关系，建立逾渗临界条件预测方程，并对方程在不同尺度研究区的应用进行了讨论和验证。结果表明：预测方程可有效地预测不同概率的逾渗临界值。同时文章在预测方程的基础上，建立了裂缝网络连通性评价标准，这对于裂缝发育地区的地下空间评价工作具有一定的指导和借鉴意义。

 

关键词: 地下空间；离散裂缝网络, 逾渗, 连通性, 临界值, 裂缝属性

Abstract: Evaluation of fracture network connectivity is an important part of studying the underground space while percolation analysis is an effective way to examine the connectivity of a fracture network. Percolation threshold of a fracture network is typically determined by indirect characterization parameters of fractures (eg., fractal dimension). However, fracture networks with different connectivity may have the same indirect characterization parameters, leading to decreased prediction reliability. To avoid this problem and to more accurately and quickly characterize fracture network connectivity, we built percolation threshold equations using direct characterization parameters (e.g., fracture length and number) by nonlinear fitting instead of using indirect characterization parameters in the simplified approach. The equations were drawn from the relationships between percolation thresholds and direct characterization parameters of different two-dimensional discrete fracture networks; application of these equations in different scaled fracture networks was discussed and validated. The results show that these equations can efficiently predict percolation thresholds of different scaled fracture networks. Based on this result, we developed criteria for estimating connectivity of fracture networks, which provide certain guidance and reference point for the evaluation of underground space in fractured areas.

Key words: underground space, discrete fracture network, percolation, connectivity, threshold, fracture properties

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