Characterizing Spatial Distributions of Fracture Apertures on Heterogeneous Rock Cores Using Positron Emission Tomography

Abstract:

The ability to transport fluids through a network of natural or induced fractures underlies many reservoir engineering technologies, including oil and gas extraction, geothermal energy utilization and nuclear waste disposal. More recently, the rapid advancement of shale gas development has highlighted the importance of fluid transport in fractures as production rates are governed by the initial fracking process. However, the fundamental physics underpinning the transport of solutes within fractures remains difficult to constrain. This is because the flows are complicated by processes such as (i) transport between the fractures and matrix, and (ii) the strong preferential flow paths through the most permeable zones within an individual fracture. Accurate interpretation of these mechanisms requires direct characterization of the rock's fracture heterogeneity. While X-ray Computed Tomography (CT) has been widely adopted to measure porosity, fluid saturation and fracture aperture distributions, applications in highly heterogeneous materials have been limited because the effects of heterogeneity are often not accounted for in the calibration or image reconstruction.

In this work, we develop an experimental platform where the spatial distributions of fracture apertures are obtained using Positron Emission Tomography (PET). To this aim, steady-state PET scans were acquired on a heterogeneous Basalt core (d = 5 cm; L = 10 cm), saturated with aqueous [¹⁸F]FDG. We show that the proposed method allows detection of minimum fractures of ~20 µm with 95% accuracy. By performing an analogous experiment with CT, it was determined that PET yields a signal-to-noise ratio that is more than one order of magnitude better than the corresponding CT measurements. Upon application of error propagation, we observed that the uncertainties increase with aperture size, giving an average uncertainty of ~20 µm when the voxel size is 500 µm; this is comparable to the errors of CT measurements for apertures of large fractures. Overall, PET imaging has a superior performance over a wide range of apertures compared to clinical CT imaging. The method presented here provides significant opportunities to characterize more challenging fracture networks, such as those that contain multiple fractures or embedded in a heterogeneous matrix.