Molecular Modeling of Subsurface Phenomena Related to Petroleum Engineering

Abstract

Experiments are always the go-to approach to reveal mysterious observations and verify new theories. However, scientific research has shifted to areas that are difficult to probe experimentally. Fortunately, computational approaches, such as molecular simulation, became available. With a rigorous theoretical foundation and microscopic insights, molecular simulation could explore unknown territories in physics and validate macroscopic theories. Grand challenges in petroleum engineering require knowledge at the molecular scale more than ever, such as the behavior of confined fluids in shale nanopores. Although it is widely used in materials science, biophysics, and biochemistry, molecular simulation has been underutilized in subsurface modeling. However, the complexity of the subsurface systems and the heterogeneity of reservoir fluids, which currently challenge both our continuum modeling approaches and experimental techniques, could benefit from molecular insights. In this Review, we briefly present the basics of molecular simulation and a few applications addressing current petroleum engineering challenges. These applications include (1) phase equilibria, where molecular simulation handles inaccessible experimental conditions such as high pressure, high temperature, or a toxic environment; (2) asphaltene aggregation, where molecular simulation enables the synthesis and evaluation of the solvent performance; (3) low-salinity water flooding, where molecular simulation reveals the key mechanisms; and (4) shale reservoirs, where molecular simulation derives the new physics controlling the transport phenomena in these reservoirs. Our goal is to demonstrate that the molecular models can shed some light on numerous subsurface applications, moving toward more predictive physics-based models to optimize and control subsurface systems.

Review on Underlying Mechanisms of Low Salinity Waterflooding: Comparisons between Sandstone and Carbonate

“…However, LSE mechanisms relevant to liquid–liquid interactions are still needed to be further investigated, especially for osmotic effect, microdispersion, and snap-off. Therefore, multiple disciplines theory should be utilized to account for these phenomena, including interfacial chemistry. Although MD simulation has been successfully applied to LSW, only focus one single crude oil component and one pure mineral. ,,, Therefore, MD simulation results are suggested based on neglecting the collaborate effects of minerals and brine compositions on LSW. In addition, experimental research should be done to verify the accuracy of MD simulation.…”

“…Although MD simulation has been successfully applied to LSW, only focus one single crude oil component and one pure mineral. ,,, Therefore, MD simulation results are suggested based on neglecting the collaborate effects of minerals and brine compositions on LSW. In addition, experimental research should be done to verify the accuracy of MD simulation.…”

High-Temperature Pyrolysis of N-Tetracosane Based on ReaxFF Molecular Dynamics Simulation

“…Molecular simulation is a computational chemistry method developed with the advance of computer technology and quantum chemistry to study the microscopic properties of molecules from the atomic level. , In order to make molecular dynamics simulations of large-scale chemical reaction systems practical, Van Duin et al developed a reaction force field (ReaxFF) system and it was shown that ReaxFF calculations are faster and the results are more accurate for small-molecule hydrocarbons. This also officially opened the application of ReaxFF method in the field of hydrocarbon microreactions.…”

AutoParams: An Automated Web-Based Tool To Generate Force Field Parameters for Molecular Dynamics Simulations

“…Nonbonded parameters include Coulomb and van der Waals forces, which are commonly calculated using a Lennard-Jones potential to allow nonbonded particles to escape an equilibrium distance with diminishing energy penalties that may be overcome by other, stronger forces . These force field parameters are also used in other calculations, such as Monte Carlo simulations , E normalt normalo normalt normala normall = ∑ normalb normalo normaln normald normals K r ( r − r e q 2 ) + ∑ normala normaln normalg normall normale normals K θ false( θ − θ eq false) 2 + ∑ normald normali normalh normale normald normalr normala normall normals V n 2 [ 1 + cos false( n ϕ − γ false) ] + ∑ i < j true[ A italicij R italicij 12 − B ij R ij 6 + q i q j ϵ R italicij ] …”