document

Abstract

A serious and complex problem in hydrocarbon recovery is the asphaltene precipitation since it affects all aspects of
petroleum production, processing, and consequently transportation. It is very desireable to predict and simulate the asphaltene
precipitation during upstream recovery processes from oil and gas reservoirs. Many models have been developed to predict
the precipitation behavior of asphaltenes.

We present implementation of an asphaltene precipitation model into a fully implicit, 3D, parallel, multiphase,
multicomponent, EOS compositional simulator called GPAS developed at the Center for Petroleum and Geosystems
Engineering to model the phase behavior and simulate the dynamic aspects of the asphaltene precipitation problem that
occurs in oil and gas reservoirs.

After studying many models for asphaltene precipitation available in the petroleum engineering literature, testing and
utilizing various simulators (e.g. ECLIPSE, CMG, VIP) to simulate the problem under primary depletion, CO2 and water
flooding scenarios, a particular thermodynamic approach was chosen to be implemented in the GPAS simulator. This model
treats the precipitating asphaltene as a single component residing in a pure solid phase, while hydrocarbon phases are
modeled with an EOS.

The primary goal of GPAS, currently under development, is to support realistic, high-resolution reservoir studies using
millions of gridcells on massively parallel computers. Key features for this simulator include the ability to handle multiple
physical models, multiple fault blocks, and flexible gridding.

With the incorporation of asphaltene simulation into GPAS, many equations in the original code were modified, added, and
implemented including the phase equilibrium, volume constraint, and mass conservation equations. Multiphase flash
calculations were developed to predict the onset point and the amount of asphaltene precipitation throughout the life of a
reservoir. Since this phenomenon severely damages the physical properties of formation, models were also implemented to
estimate the effects on porosity, relative permeability, and wettability. The fully implicit formulations of GPAS added a great
deal to the complexity of the formulations.

Simulation results indicate that asphaltene precipitation reduces oil production. A key conclusion of the achivements is the
capability to predict the detrimental effects of asphaltenes in reservoirs without the need for data generation from expensive
downhole samples. This research also led to a more powerful reservoir simulator that can be used by E&P companies to
predict asphaltene precipitation in reservoirs and help with the design of primary and secondary recovery processes on their
desktops or clusters of computers to solve E&P challenges of the future.