Investigation of uncertainty in CO2 reservoir models: A sensitivity analysis of relative permeability parameter values

Numerical reservoir models of CO2 injection in saline formations rely on parameterization of laboratory measured pore-scale processes. We performed a parameter sensitivity study and Monte Carlo simulations to determine the normalized change in total CO2 injected using the finite element heat and mass-transfer code (FEHM) numerical reservoir simulator. Experimentally measured relative permeability parameter values were used to generate distribution functions for parameter sampling. The parameter sensitivity study analyzed five different levels for each of the relative permeability model parameters. All but one of the parameters changed the CO2 injectivity by <10%, less than the geostatistical uncertainty that applies to all large subsurface systems due to natural geophysical variability and inherently small sample sizes. The exception was the end-point CO2 relative permeability, k(r,CO2)(0) the maximum attainable effective CO2 permeability during CO2 invasion, which changed CO2 injectivity by as much as 80%. Similarly, Monte Carlo simulation using 1000 realizations of relative permeability parameters showed no relationship between CO2 injectivity and any of the parameters but k(r,CO2)(0), which had a very strong (R-2 = 0.9685) power law relationship with total CO2 injected. Model sensitivity to k(r,CO2)(0), points to the importance of accurate core flood and wettability measurements. (C) 2016 Elsevier Ltd. All rights reserved.