Comparison of Fracture Network Properties of Genetic and Poisson DFN Modeling at the KAERI Underground Research Tunnel, Korea

ABSTRACT: Genetic discrete fracture network (G-DFN) modeling generates fracture networks structured by abutments or T-intersections through growth simulations, whereas conventional Poisson DFN (P-DFN) modeling produces spatially uncorrelated fractures. This structural distinction underlies the conceptual framework of DFN modeling, shaping field data interpretation and, consequently, the resulting DFN geometry and flow behavior, which are critical factors for the deep geological disposal of nuclear waste. This study compares the G-DFN and P-DFN modeling approaches at the Korea Atomic Energy Research Institute (KAERI) Underground Research Tunnel (KURT), independently applying each method with minimal shared assumptions to ensure each DFN is generated based on its respective framework. Using the face mapping from the KURT access tunnel, each approach resulted in distinct DFNs with differences in fracture intensity, size, and spatial distribution. In terms of their hydraulic properties, the G-DFNs provided a closer match to the hydraulic conductivity distribution of borehole flow tests. Overall, this comparison demonstrates that the G-DFN and P-DFN modeling approaches result in DFNs with notable differences in geometric and hydraulic properties, with the G-DFN providing a geologically consistent alternative that better represents the fracture network at the KURT.