Numerical models for flow in the subsurface must tackle the inherent complexity of geological strata in which the CO2 will be stored, much as weather forecasts must cope with the impact of very small-scale turbulent flows in making predictions over countries or regions. This need to parameterise geological complexity has lead to a range of models, from complex reservoir simulators commonly used in the oil and gas industry appropriate for smaller scale or shorter time frame injections, to reduced models which accurately capture the large, and long timescale migration of buoyant CO2. Through a process of comparing these models across length and time scales, and importantly by comparing their simulation results with the remote observations of CO2 spreading in the field we can produce accurate and efficient methods of assessing the ultimate fate of CO2 in the subsurface.
CO2 modelling software assessment will use the correct physics, starting a design process to make better software predicting CO2 saturation and spread. Efficient use, and handover, of CO2 storage sites relies on conformance to modelled predictions. The models are not accurate across 1010 size scales required. CO2 modelling software (e.g. ECLIPSE, TOUGH) is derived from hydrocarbon and radwaste applications, where induced pressure gradients from the injecting or producing wellbores dominate the flow field, and where flow is dominated by modal permeability, not for CO2 top decile permeability. These models are not correct for modelling CO2-brine flow, pressure, pore accumulation, and lateral migration on the much larger 10-100 km scales characteristic of North Sea reservoirs where buoyancy-driven flow dominates. A simplified numerical framework will be adopted which maximises attention on horizontal resolution by analytically parameterising the vertical structure of the CO2 plume. Upscaling of processes and buoyant migration through permeability and capillarity heterogeneities, will be incorporated from WPs B1 and B2. A computationally efficient architecture will be designed to scale-up Big Data available from micro-scale imaging into a digital rock model, and then convert to size scales incorporating seismic attributes and uncertainty. It is intended that results will feed into an application to RCUK, to develop advanced CO2-specified software.