Fracture size and transmissivity correlations: Implications for transport simulations in sparse three‐dimensional discrete fracture networks following a truncated power law distribution of fracture size. Issue 8 (25th August 2016)

• Record Type: Journal Article
• Authors: Hyman, J. D.; Aldrich, G.; Viswanathan, H.; Makedonska, N.; Karra, S.
• Is Part Of: Water resources research. Volume 52:Issue 8(2016:Aug.)
• Page Start: 6472
• Page End: 6489
• Publication Date: 2016-08-25
• Subjects: discrete fracture neworks -- subsurface flow and transport -- fractured rock -- transmissivity; Hydrology -- Periodicals; 333.91
• DOI: 10.1002/2016WR018806
• Languages: English
• ISSNs: 0043-1397

Abstract

Abstract: We characterize how different fracture size‐transmissivity relationships influence flow and transport simulations through sparse three‐dimensional discrete fracture networks. Although it is generally accepted that there is a positive correlation between a fracture's size and its transmissivity/aperture, the functional form of that relationship remains a matter of debate. Relationships that assume perfect correlation, semicorrelation, and noncorrelation between the two have been proposed. To study the impact that adopting one of these relationships has on transport properties, we generate multiple sparse fracture networks composed of circular fractures whose radii follow a truncated power law distribution. The distribution of transmissivities are selected so that the mean transmissivity of the fracture networks are the same and the distributions of aperture and transmissivity in models that include a stochastic term are also the same. We observe that adopting a correlation between a fracture size and its transmissivity leads to earlier breakthrough times and higher effective permeability when compared to networks where no correlation is used. While fracture network geometry plays the principal role in determining where transport occurs within the network, the relationship between size and transmissivity controls the flow speed. These observations indicate DFN modelers should be aware that breakthrough times and effective permeabilities can be strongly influenced by such a relationship in addition to fracture and network statistics. Key Points: Breakthrough times and effective permeabilities in DFN simulations are influenced by the adopted relationship between size and aperture Correlated relationship resulted in higher effective permeability values and earlier breakthrough times than networks without correlation Fracture geometry controls where transport occurs in a DFN while the adopted relationship controls the speed of flow and transport times