While seepage poses significant challenges to many geotechnical projects and hydraulic conductivity is a key soil property, the fundamental pore-scale understanding of the water flow in soil is poor. The seepage velocities considered in geotechnical engineering are area-averaged flow rates and their relation to the actual fluid velocity is unclear. Some of the predictive formulae for sand currently used in engineering practice were developed using simplified particle-scale analytical models whose validity is not well-established. Recent advances in modelling and imaging enable these uncertainties associated with seepage to be addressed and this paper proposes a first principles simulation approach in which the flow in the void space is modelled by applying Computational Fluid Dynamics (CFD) to void geometries obtained using X-ray micro-Computed Tomography (microCT). The model was verified by comparing it to hydraulic conductivity data from laboratory permeameter tests on the same materials. The generated data provide significant sub-particle-scale insight into fluid velocities and head loss. The results are used to show that the existing models for predicting hydraulic conductivity struggle to account for the full range of particle variables and fail to explain the true governing variables, which relate to the micro-scale properties of the void space.