Molecular Simulation towards Efficient and Representative Subsurface Reservoirs Modeling
AuthorsKadoura, Ahmad Salim
ProgramEarth Sciences and Engineering
KAUST DepartmentPhysical Science and Engineering (PSE) Division
Permanent link to this recordhttp://hdl.handle.net/10754/621235
MetadataShow full item record
AbstractThis dissertation focuses on the application of Monte Carlo (MC) molecular simulation and Molecular Dynamics (MD) in modeling thermodynamics and flow of subsurface reservoir fluids. At first, MC molecular simulation is proposed as a promising method to replace correlations and equations of state in subsurface flow simulators. In order to accelerate MC simulations, a set of early rejection schemes (conservative, hybrid, and non-conservative) in addition to extrapolation methods through reweighting and reconstruction of pre-generated MC Markov chains were developed. Furthermore, an extensive study was conducted to investigate sorption and transport processes of methane, carbon dioxide, water, and their mixtures in the inorganic part of shale using both MC and MD simulations. These simulations covered a wide range of thermodynamic conditions, pore sizes, and fluid compositions shedding light on several interesting findings. For example, the possibility to have more carbon dioxide adsorbed with more preadsorbed water concentrations at relatively large basal spaces. The dissertation is divided into four chapters. The first chapter corresponds to the introductory part where a brief background about molecular simulation and motivations are given. The second chapter is devoted to discuss the theoretical aspects and methodology of the proposed MC speeding up techniques in addition to the corresponding results leading to the successful multi-scale simulation of the compressible single-phase flow scenario. In chapter 3, the results regarding our extensive study on shale gas at laboratory conditions are reported. At the fourth and last chapter, we end the dissertation with few concluding remarks highlighting the key findings and summarizing the future directions.