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.

Complex flow dynamics have been observed, at the pore-scale, during multiphase through porous rocks. These dynamics are not captured in large scale models exploring the migration and trapping of subsurface fluids e.g., CO2 or hydrogen. Due to limitations in imaging capabilities, these dynamics cannot be observed directly at the larger, Darcy scale. Instead, by using pressure data from pore-scale (mm-scale) and core-scale (cm-scale) experiments, we show that fluctuations in pressure measured at the core-scale reflect specific fluid displacement events taking place at the pore-scale. The spectral characteristics of the pressure data depends on the flow dynamics, size of the rock sample, and heterogeneity of pore space. While high resolution imaging of large samples would be useful in assessing flow dynamics across many of the scales of interest, such an approach is currently infeasible. We suggest an alternative, pragmatic, approach examining pressure data in the time-frequency domain using wavelet transformation.

Many subsurface fluid flows, including the storage of CO underground or the production of oil, are transient processes incorporating multiple fluid phases. The fluids are not in equilibrium meaning macroscopic properties such as fluid saturation and pressure vary in space and time. However, these flows are traditionally modelled with equilibrium (or steady-state) flow properties, under the assumption that the pore scale fluid dynamics are equivalent. In this work, we used fast synchrotron X-ray tomography with 1s time resolution to image the pore scale fluid dynamics as the macroscopic flow transitioned to steady-state. For nitrogen or decane, and brine injected simultaneously into a porous rock we observed distinct pore scale fluid dynamics during transient flow. Transient flow was found to be characterised by intermittent fluid occupancy, whereby flow pathways through the pore space were constantly rearranging. The intermittent fluid occupancy was largest and most frequent when a fluid initially invaded the rock. But as the fluids established an equilibrium the dynamics decreased to either static interfaces between the fluids or small-scale intermittent flow pathways, depending on the capillary number and viscosity ratio. If the fluids were perturbed after an equilibrium was established, by changing the flow rate, the transition to a new equilibrium was quicker than the initial transition. Our observations suggest that transient flows require separate modelling parameters. The timescales required to achieve equilibrium suggest that several metres of an invading plume front will have flow properties controlled by transient pore scale fluid dynamics.

We employ a multi scale approach combining experiments and modelling to elucidate the impacts of small scale (sub-seismic resolution <10m) capillary pressure heterogeneities in field scale CO2 flow and trapping. We analyse 48 rock cores (~3cm length, 4cm diameter) covering the entire 100m interval of the Captain D sandstone in the Goldeneye field, UK North Sea. We experimentally measure porosity, capillary pressure, absolute permeability, relative permeability and trapping characteristics for the cores, which are used to create 3D numerical models with heterogeneities defined at the mm scale. These models are validated by predicting experimental X-Ray CT observations of saturation (mm scale) and pressure measurements (cm scale) at various flow rates and fractional flows of gas-water. The intrinsic, core scale properties are then used to populate 2D meso scale numerical simulations (50m x 10m size), with heterogeneities defined at cm scale using a geostatistical representation. We vary the correlation length and variance of the fields within the bounds of the experimental observations to investigate the impacts of small scale heterogeneity on vertical and lateral CO2 plume migration under different Capillary, Bond and Gravity numbers. At low flow potential, layered capillary pressure heterogeneities can speed up lateral plume migration by up to 20%, with gravitational segregation significantly enhancing the migration (See Fig. 1). In the vertical case, layered heterogeneities can significantly increase CO2 trapping, which is further enhanced with the inclusion of capillary pressure hysteresis. Finally, we derive capillary limit, upscaled equivalent properties from the meso scale simulations, which incorporate the impacts of small scale heterogeneity. These are used to represent the grid block properties in a full field 3D numerical model of the Goldeneye field (lateral ~5 km, depth 200m). We analyse the impact of varying relative permeabilities (with anisotropy) on the field scale plume migration and trapping. We see large differences compared to cases using intrinsic rock properties, indicating that proper inclusion of small scale heterogeneity is needed in upscaling workflows when predicting and assessing uncertainty in low flow potential CO2 plume migration at the field scale.

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.