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Episodes 2021; 44(2): 99-106

Published online June 1, 2021


Copyright © International Union of Geological Sciences.

Effects of conditioning on the equivalent properties estimated by a discrete fracture network model

Sung-Hoon Ji*

Radioactive Waste Disposal Research Division, Korea Atomic Energy Research Institute, Daejeon, 34057, Republic of Korea

Correspondence to:*E-mail: shji@kaeri.re.kr

Received: April 5, 2020; Revised: June 26, 2020; Accepted: June 26, 2020

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.


The classical stochastic discrete fracture network (DFN) approach is an attempt to simulate the statistical characteristics of fractures in a site, and does not need to match the observed fractures. In this study, the effects of conditioning the stochastically generated fractures with the fracture mapping and geophysical survey data on the equivalent properties of a fracture system were evaluated. A hypothetical real fracture system was assumed, and the classical and conditional stochastic approaches were applied to simulate it. Then the equivalent network properties such as equivalent permeability and density of the percolating cluster were calculated and compared to each other. The comparison results showed that conditioning with the fracture mapping data improved the classical stochastic approach in estimating the geometric connection by the fracture network while the performance of the conditional stochastic models estimating the hydraulic connection was similar to the classical stochastic model.