19–22 May 2025
US/Mountain timezone

Understanding the influence of fracture network characteristics and fluid density on solute transport in sedimentary fractured rocks

22 May 2025, 15:45
1h 30m
Poster Presentation (MS08) Mixing, dispersion and reaction processes across scales in heterogeneous and fractured media Poster

Speaker

Porraket Dechdacho (University of Minnesota)

Description

Complex interactions between geological heterogeneity and fluid properties govern flow and transport in fractured media. These dynamics are critical for applications such as contaminant remediation, enhanced geothermal systems, and geologic carbon sequestration, where density-driven flow can impact transport. Under these conditions, fracture network characteristics significantly control flow paths by inducing preferential flow and contributing non-Fickian transport. Although previous studies have examined the effects of fracture network properties and density-driven flow, we still lack fundamental knowledge about the effects of sedimentary rock features, such as vertical fractures and bedding plane fractures on solute transport.

We developed field-inspired three-dimensional discrete fracture networks (3D DFN) using dfnWorks to systematically investigate how fracture network properties affect solute transport under variable-density flow conditions. The ensembles of DFN models were generated and incorporated fracture and matrix attributes. The domain consists of two 25 m-thick layers representing fractured sedimentary-rock aquifers with four fracture sets: (1) bed parallel parting horizontal fractures (BPP), (2) a vertical injection fracture at the inlet, (3) two sets of stochastic vertical fractures terminated at the layer contacts. PFLOTRAN was used to simulate a pulse injection and transport of tracer into a saturated domain with ambient flow. We examined two structural characteristics: fracture intensity (P32 = 0.01, 0.05, and 0.5) and the presence of BPP, as well as hydrogeological properties, particularly the ratio of vertical to horizontal fracture permeability, under conditions with and without density contrast. Solute breakthrough curves and mass partitioning between fractures and matrix were analyzed to evaluate transport behavior.

The results revealed that BPP significantly influences flow and transport in low- and medium-P32 networks but has a minimal effect in high-P32 networks. In low and medium P32, BPP induces strong preferential flow, resulting in early solute arrival and multi-modal breakthrough behavior, which is absent without BPP. In addition to BPP, transport is significantly controlled by unique flow paths created by a random distribution of a few vertical fractures, which also cause lower and slower mass recovery. However, a high permeability contrast between vertical fractures and BPP mitigates these unique path effects by limiting solute transport into vertical fractures, promoting a more uniform BPP-dominated flow. In highly fractured networks, the influence of BPP diminishes as enhanced fracture connectivity creates less channelization and more uniform flow throughout the domain, resembling homogeneous media and producing higher and faster mass recovery. However, reducing vertical fracture permeability enhances the influence of BPP and increases flow path heterogeneity, emphasizing the importance of hydrogeological properties in controlling transport. Compared to structural and hydrological factors, the effects of density-driven flow on solute transport were insignificant across all scenarios due to strong dominant fracture flow, especially BPP.

Our findings highlight the role of fracture network characteristics and hydrogeological properties in controlling flow and transport in fractured sedimentary aquifers, where density effects are negligible, as preferential flow paths and permeability contrasts, widely observed in the field, dominate overall flow. However, conclusions may vary slightly under different head gradients that influence fracture flow.

Country United States
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Primary author

Porraket Dechdacho (University of Minnesota)

Co-authors

Jeffrey Hyman (Los Alamos National Laboratory) Matthew Sweeney (Los Alamos National Laboratory) Peter Kang (University of Minnesota)

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