From outcrops and laboratory rock samples to three-dimensional fracture and flow pathway modelling

Discontinuities, i.e. fractures, form the dominant pathways for fluid flow within crystalline bedrock. Characterizing these fracture networks involves integrating data across multiple scales. Field observations from outcrops yield macroscopic structural data, often analysed in two dimensions for geometric and topological properties using tools like fractopo (Ovaskainen 2023). Complementary three-dimensional data comes from oriented drillcores, while X-ray computed tomography (CT) imaging of laboratory rock samples provides crucial microscale details of fracture geometry and rock matrix properties. To understand fluid behaviour at larger scales relevant to practical applications, discrete fracture network (DFN) modelling is often necessary. However, constructing and simulating flow within these three-dimensional fracture models presents challenges. The required software can be complex, often proprietary, while free and open-source alternatives may lack user-friendliness or sustained development.

Predicting fluid flow pathways accurately through fractured rock is essential for the safety of, e.g., geological disposal of nuclear waste, geothermal energy extraction and management of groundwater resources. A gap exists between the multi-scale field, laboratory and digitized datasets geologists can collect and the use of these observations in three-dimensional fracture and flow pathway modelling. Solutions exist, especially as proprietary software but those lack transparency due to the closed-source nature. Bridging this gap is crucial for improving the reliability of subsurface flow predictions. Furthermore, more effort is required to effectively translate the detailed data a geologist captures, encompassing field observations, digitized outcrop fracture traces, and laboratory rock sample scans, into comprehensive, upscaled, three-dimensional fracture network models, for instance, through the use of DFN-modelling.

This research focuses on coupling field observations with laboratory rock sample CT-scans and flow experiments. We have characterized fracture networks at the macroscale from outcrops using established 2D analysis techniques (E.g., Ovaskainen et al. 2023). Concurrently, we have analysed microscale fracture characteristics and rock properties from laboratory rock samples using X-ray CT imaging. Our current work involves integrating these distinct datasets, which capture both field-scale distributions and lab-scale details, into preliminary three-dimensional fracture network models and flow simulations using free and open-source tools, such as MPLBM-UT (Santos et al. 2022). The emphasis has firstly been on trying to inform model construction through a geological lens, rather than focusing solely on mathematical or computational abstractions and, secondly, to use free and open-source software for this purpose to attempt to bridge the gap between the field, lab and models for a more wider field of experts.

Ovaskainen, Nikolas. 2023. “Fractopo: A Python Package for Fracture Network Analysis.” Journal of Open Source Software 8 (85): 5300. https://doi.org/10.21105/joss.05300.

Ovaskainen, Nikolas Aleksi, Pietari Mikael Skyttä, Nicklas Johan Nordbäck, and Jon Oskar Engström. 2023. “Detailed Investigation of Multi-Scale Fracture Networks in Glacially Abraded Crystalline Bedrock at Åland Islands, Finland.” Solid Earth 14 (6): 603–24. https://doi.org/10.5194/se-14-603-2023.

Santos, Javier E., Alex Gigliotti, Abhishek Bihani, Christopher Landry, Marc A. Hesse, Michael J. Pyrcz, and Maša Prodanović. 2022. “MPLBM-UT: Multiphase LBM Library for Permeable Media Analysis.” SoftwareX 18 (June): 101097. https://doi.org/10.1016/j.softx.2022.101097.