Molecular dynamics analysis of compositional effects in hydrocarbon systems property calculations

• Proposed an engineering approach via MD to obtain fluid properties for EOR processes.
• Showed many advantages to generate PVT and non-equilibrium mixing properties.
• Illustrated subtle compositional microstructure phenomena from MD analysis.
• Quantified the complex compositional effects on diffusion and viscosity.

Fluid pressure–volume–temperature (PVT) properties are essential for enhanced oil recovery (EOR) process description, particularly for the development of new recovery processes such as solvent injection. However there remains significant uncertainty in laboratory experimental data, such as that associated with light and heavier components mixing processes. Much of this uncertainty may be attributed to the multicomponent nature of most oils and the existence of micro-structures in real dynamic systems.Here, an alternate engineering approach is proposed and illustrated to obtaining this required data, which can be used as an alternative to, or in conjunction with, expensive and time-consuming direct experimental measurements. This method utilizes the molecular dynamics (MD) method to setup dynamic simulation models for a variety of hydrocarbon systems. More particularly, 16 single phase (both single and multicomponent) MD hydrocarbon systems are considered, as well as 3 biphasic (methane–decane) MD systems to quantify aspects of dynamic mixing. The impact of a variety of oil chemical structures (normal and branched alkanes, cycloalkanes, aromatic, and polar) on fluid property predictions is thereby highlighted, with implications for future additional complex oils analysis.With these systems, a large range of equilibrium and non-equilibrium properties under different T, P and compositional scenarios have been predicted, and good agreement with available laboratory experimental data has been demonstrated here. Indications of subtle microstructure phenomena are also obtained from our MD analysis. As the resultant MD data represent many years of costly experimental measurements, this points to a new cost-efficient approach in obtaining necessary EOR parameters, to be used in conjunction with limited targeted experiments.