Molecular Dynamics (MD) simulations were used in conjunction with the Kirkwood-Buff (KB) theory to compute partial molar volume (PMV) for solutes of various chemical natures. Simulations performed with only the Lennard-Jones (LJ) potential yield PMV for solutes which coincide with the cavity volumes derived from calculations with scaled particle theory (SPT). Whereas, simulations carried out with only the repulsive LJ term produced PMV of solutes closer to their excluded volumes. We also determined the thermal volume, VT, which represents the volume of the effective void created around solutes of varying cavity sizes and applied the spherical approximation of solute geometry to evaluate the thickness of the thermal volume, . Our results reveal an increase in the thickness of thermal volume, , with an increase in the size of the solute. Our theoretical results are in good agreement with the reported empirical schemes for parsing PMV data on small solutes.

Molecular Dynamics (MD) simulations were used in conjunction with the Kirkwood-Buff (KB) theory to compute partial molar volume (PMV) for solutes of various chemical natures. Simulations performed with only the Lennard-Jones (LJ) potential yield PMV for solutes which coincide with the cavity volumes derived from calculations with scaled particle theory (SPT). Whereas, simulations carried out with only the repulsive LJ term produced PMV of solutes closer to their excluded volumes. We also determined the thermal volume, VT, which represents the volume of the effective void created around solutes of varying cavity sizes and applied the spherical approximation of solute geometry to evaluate the thickness of the thermal volume, . Our results reveal an increase in the thickness of thermal volume, , with an increase in the size of the solute. Our theoretical results are in good agreement with the reported empirical schemes for parsing PMV data on small solutes.

Numerical simulation has been used, as common practice, to estimate the CO2 storage capacity of depleted reservoirs. However, this method is time consuming, expensive and requires detailed input data. This investigation proposes an analytical method to estimate the ultimate CO2 storage in depleted oil and gas reservoirs by implementing a volume constrained thermodynamic equation of state (EOS) using the reservoir?s average pressure and fluid composition. This method was implemented in an algorithm which allows fast and accurate estimations of final storage, which can be used to select target storage reservoirs, and design the injection scheme and surface facilities. Impurities such as nitrogen and carbon monoxide, usually contained in power plant flue gases, are considered in the injection stream and can be handled correctly in the proposed algorithm by using their thermodynamic properties into the EOS. Results from analytical method presented excellent agreement with those from reservoir simulation. Ultimate CO2 storage capacity was predicted with an average difference of 1.3%, molar basis, between analytical and numerical methods; average oil, gas, and water saturations were also matched. Additionally, the analytical algorithm performed several orders of magnitude faster than numerical simulation, with an average of 5 seconds per run.