LAUSR

Abstract Numerical models are a critical tool for forecasting subsurface multiphase flow associated with geologic carbon storage. The uncertainty of model results stems from many factors, including uncertainty in multiphase flow parameters. Specifically, relative permeability and capillary pressure relationships depend on both the rock properties and fluid properties, and the latter may be highly nonlinear as fluid temperature, and pressure conditions change. Forecasts of trapping mechanisms, phase behavior, and plume movement are impacted by choice of relative permeability and capillary pressure functions and how those functions are calibrated and constrained. In particular, one of the most neglected aspects of such simulations is meaningful capillary pressure processes. A primary goal of this study is to quantify the difference in forecasts for models that utilize capillary pressure functions calibrated with measured data from the results of models without such. Additionally, the relative permeability models developed here were derived from measured capillary pressure data. Those data were used to constrain saturation endpoints in the relative permeability curves and dictate how that relative permeability was distributed spatially. The main conclusions drawn from this analysis include (1) heterogeneity in relative permeability plays a significant role in simulated forecasts of CO2 migration, trapping mechanisms and storage capacity, as well as oil and water production, and (2) capillary pressure, and in particular, the magnitude of capillarity also plays a significant role in these processes. Conversely, if the magnitude of capillarity is small relative to in situ fluid pressures, it imparts insignificant effects on these processes.