Development of a fully implicit, parallel, equation-of-state compositional simulator to model asphaltene precipitation in petroleum reservoirs



Journal Title

Journal ISSN

Volume Title



Asphaltene precipitation is a serious and complex problem in oil recovery that affects all aspects of oil production, processing and transportation. It is very important to predict the asphaltene precipitation during the production process. Many models have been developed to predict the precipitation behavior of asphaltene. In this work we present implementation of asphaltene precipitation model into a fully implicit, three-dimensional, multiphase, multicomponent, parallel, equation-of-state compositional simulator called GPAS, developed at the Center for Petroleum and Geosystems Engineering at The University of Texas at Austin. The primary goal of GPAS, currently under development, is to support realistic, high-resolution reservoir studies with a million or more gridblocks on massively parallel computers. Key requirements for this simulator include the ability to handle multiple physical models, generalized well management, multiple fault blocks, and flexible gridding. GPAS is developed under the framework named IPARS (Integrated Parallel Accurate Reservoir Simulator) and is constructed using a Newton-type formulation. The Peng-Robinson EOS is used for the hydrocarbon phase behavior calculations. The linear solvers from PETSc package (Portable Extensible Toolkit for Scientific Computation) are used for the solution of the underlying linear equations. The framework provides input/output, table lookups, FORTRAN array memory allocation, domain decomposition, and message passing between processors for updating physical properties in massbalance equations in overlapping regions. PETSc handles communications between processors needed for the linear solver. After studying many available models in the literature for asphaltene precipitation, Nghiem's model was chosen for modeling asphaltene precipitation in GPAS. We believe this implementation has led to a more powerful reservoir simulator that can be used to predict asphaltene precipitation by small and large oil companies to help them in the design of complex gas and waterflooding processes on their desktops or a cluster of computers. Nghiem's model is a solid model that treats the precipitating asphaltene as a single component residing in the solid phase while oil and gas phases are modeled with a cubic EOS. Solid models may require many empirical parameters and a large amount of tuning to match experimental data. Since asphaltene precipitation severely reduces both absolute permeability and relative permeability, it is important to simulate the precipitation behavior of asphaltenes during the oil production process. Many models have been developed to predict the onset point and the amount of asphaltene precipitation as well as the change in relative permeability. In this study, physical properties models were also implemented in GPAS to estimate the effect of asphaltene precipitation on permeability in order to calculate the amount of precipitation during oil production. Compositional simulation results with asphaltene precipitation model indicate that asphaltene precipitation may damage the oil production in most cases. A key conclusion of the findings is the ability to predict the deposition of asphaltenes in the reservoir without the need for generating data from expensive downhole samples.