Development of a Predictive Model for Carbon Dioxide Sequestration in Deep Saline Carbonate Aquifers

Abstract

Abstract Increase in CO2 concentration in the atmosphere is the widespread concern due to its global warming effect. CO2injection into deep saline aquifers is one of the preferable ways to mitigate the CO2 emission since CO2 is in supercritical state and larger volumes of CO2 can be stored due to its high density. Several numerical simulations are needed before injection to determine the storage capacity of a saline aquifer. Since numerical simulations are very expensive and time consuming, developing a predictive model can be very useful to quick estimation of CO2storage capacity of a deep saline aquifer. To create a predictive model, ranges and limits of rock properties (porosity, permeability, vertical to horizontal permeability ratio), fluid properties (irreducible water saturation, gas permeability end point, Corey water and gas exponents), reaction properties (forward and backward reaction rates) and reservoir properties (depth, pressure gradient, temperature gradient, formation dip angle, salinity), diffusion coefficient and Kozeny-Carman Coefficient that affect the CO2 storage capacity are determined from published literature data. Other parameters such as pore volume compressibility and density of brine are calculated from correlations. To cover all possibilities, Latin Hypercube Space Filling Design is used to construct 100 simulations developed using CMG STARS for 300 years of CO2 injection. By using least squares method, a linear correlation with a correlation coefficient 0.81 is found to calculate CO2 storage capacity of the deep saline carbonate aquifers by using aforementioned simulation variables. Numerical dispersion effects have been considered by increasing the grid dimensions. It has been found that correlation coefficient decreased to 0.78 when the grid size was increased from 250 ft to 750 ft. The sensitivity analyses showed that the most important parameter that affects CO2 storage capacity is depth since the pressure difference between formation pressure and fracture pressure increases with depth. It was observed that most of the gas (up to 90%) injected into the aquifer formation dissolves into the formation water and negligible amount of CO2 reacts with carbonate. This result is in accord with sensitivity analyses as the variables affecting the solubility of CO2 in brine have greater affect on storage capacity of aquifers. Dimensionless linear and nonlinear predictive models were constructed to estimate the CO2 storage capacity of a deep saline carbonate aquifer and it was found that the best dimensionless predictive model is a linear model that is independent of bulk volume of the aquifer.