Field-scale observations suggest that rock heterogeneities control subsurface fluid flow, and these must be characterised for accurate predictions of fluid migration, such as during \CO2 sequestration. Recent efforts have focused on simulation-based inversion of laboratory observations with X-ray imaging, but models produced in this way have been limited in their predictive ability for heterogeneous rocks. We address the main challenges in this approach through an algorithm that combines: a 3-parameter capillary pressure model, spatial heterogeneity in absolute permeability, the constraint of history match iterations based on marginal error improvement, and image processsing that incorporates more of the experimental data in the calibration. We demonstrate the improvements on five rocks (two sandstones and three carbonates), representing a range of heterogeneous properties, some of which could not be previously modelled. The algorithm results in physically representative models of the rock cores, reducing non-systematic error to a level comparable to the experimental uncertainty.

Predictive modelling of subsurface CO2 flow is used for optimising the design of geological CO2 storage projects e.g. with respect to mass stored and long term security. However several field scale projects have reported plume dynamics that do not match numerical predictions. Previous work has indicated that upscaling capillary heterogeneity results in different plume dynamics in synthetic 2D cross-sections and at early times (<0.2PV injected). Here we extend the workflow to 3D and analyse the impacts of longer term flow behaviour in an industrial scale geological carbon storage site with multi-point CO2 injection, structural relief and realistic flow rates. The models reveal that capillary heterogeneity in horizontally layered lithologies enhance channel formation, increases reservoir sweep, and reduces vertical migration speed near the injectors, all of which improve storage efficiency. At distances far from the injectors, the plume travels faster as a result of the heterogeneity. The results also show that simulations in 3D have qualitatively distinct results from those in 2D due to the increase in flow pathways.

The characterisation of multiphase flow properties is essential for predicting large-scale fluid behaviour in the subsurface. Insufficient representation of small-scale heterogeneities has been identified as a major gap in conventional reservoir simulation workflows. Capillary heterogeneity has an important impact on small-scale flow and is one of the leading causes of anisotropy and flow rate dependency in relative permeability. We evaluate the workflow developed by Jackson et al. (2018) for use on rocks with complex heterogeneities. The workflow characterises capillary heterogeneity at the millimetre scale. The method is a numerical history match of a coreflood experiment with the 3D saturation distribution as a matching target and the capillary pressure characteristics as a fitting parameter. Coreflood experimental datasets of five rock cores with distinct heterogeneities were analysed: two sandstones and three carbonates. The sandstones exhibit laminar heterogeneities. The carbonates have isotropic heterogeneities at a range of length scales. We found that the success of the workflow is primarily governed by the extent to which heterogeneous structures are resolved in the X-ray imagery. The performance of the characterisation workflow systematically improved with increasing characteristic length scales of heterogeneities. Using the validated models, we investigated the flow rate dependency of the upscaled relative permeability. The findings showed that the isotropic heterogeneity in the carbonate samples resulted in non-monotonic behaviour; initially the relative permeability increased, and then subsequently decreased with increasing flow rate. The work underscores the importance of capturing small-scale heterogeneities in characterising subsurface fluid flows, as well as the challenges in doing so.