Investigation of uncertainty in CO 2 reservoir models: A sensitivity analysis of relative permeability parameter values
Numerical reservoir models of CO 2 injection in saline formations rely on parameterization of laboratory-measured pore-scale processes. Here, we have performed a parameter sensitivity study and Monte Carlo simulations to determine the normalized change in total CO 2 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 CO 2 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 CO 2 relative permeability, k$0\atop{r}$ CO2 , the maximum attainable effective CO 2 permeability during CO 2 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 CO 2 injectivity and any of the parameters but k$0\atop{r}$ CO2 , which had a very strong (R 2 = 0.9685) power law relationship with total CO 2 injected. Model sensitivity to k$0\atop{r}$ CO2 points to the importance of accurate core flood and wettability measurements.