4.7 Article

Method for Generating a Discrete Fracture Network from Microseismic Data and its Application in Analyzing the Permeability of Rock Masses: a Case Study

期刊

ROCK MECHANICS AND ROCK ENGINEERING
卷 52, 期 9, 页码 3133-3155

出版社

SPRINGER WIEN
DOI: 10.1007/s00603-018-1712-x

关键词

Discrete fracture network; Focal mechanism; Fracture seepage; Permeability

资金

  1. National Key Research and Development Program of China [2016YFC0801602, 2017YFC1503100]
  2. National Natural Science Foundation of China [51574060, 51604062]
  3. China Scholarship Council [201706080101]

向作者/读者索取更多资源

The deformation and failure process of rock masses is accompanied by the initiation, propagation and connection of fractures. The behaviors of fractures under engineering disturbance can be effectively determined by microseismic (MS) monitoring, and such information is essential for the stability analysis of rock masses. Based on moment tensor theory, the geometric properties of focal planes and the failure mechanisms of the seismic source can be determined, and this study proposes criteria for extracting the reasonable fracture from focal planes associated with different failure mechanisms and provides a detailed example. The fracture identified by the proposed criteria is called MS-derived fracture, and a formula describing the aperture is derived from the moment tensor theory and the motion characteristics of the MS-derived fractures associated with different failure mechanisms. This work chose the Shirengou Iron Mine as a case and selected an area exhibiting seepage and rock mass failure as the study area. Based on a three-dimensional noncontact discontinuity scan, a natural discrete fracture network (DFN) was generated. With the help of the proposed fracture generation method, a new DFN based on MS data was generated and is referred to as the MS-derived DFN. With the aid of Oda's theory, the changes in the permeability value, principal direction and anisotropy degree in the study area were analyzed based on the MS-derived DFN, and the seepage channels in the study area were also determined. Therefore, the research methods in this paper could be used to better understand the changes in the permeability of rock masses based on MS data.

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