Summary
A fully implicit, parallel, compositional reservoir simulator has been
developed that includes both a cubic equation of state model for the
hydrocarbon phase behavior and Hand’s rule for the surfactant/oil/brine phase
behavior. The aqueous species in the chemical model include surfactant,
polymer, and salt. The physical property models include surfactant/oil/brine
phase behavior, interfacial tension, viscosity, adsorption, and relative
permeability as a function of trapping number. The fully implicit simulation
results were validated by comparison with results from our IMPEC chemical
flooding simulator (UTCHEM). The results indicate that the simulator scales
well using clusters of workstations. Also, simulation results from parallel
runs are identical to those using a single processor. Field-scale
surfactant/polymer flood simulations were successfully performed with over
1,000,000 gridblocks using multiple processors.
Introduction
Chemical flooding is a method to improve oil recovery that involves the
injection of a solution of surfactant and polymer followed by a polymer
solution. The surfactant causes the mobilization of oil by decreasing
interfacial tension, whereas the polymer increases the sweep efficiency by
lowering the mobility ratio. Chemical flooding has the potential to recover a
very high fraction of the remaining oil in a reservoir, but the process needs
to be designed to be both cost effective and robust, which requires careful
optimization. Several reservoir simulators with chemical flooding features have
been developed as a tool for optimizing the design (Delshad et al. 1996;
Schlumberger 2004; Computer Modeling 2004). The University of Texas chemical
flooding simulator, UTCHEM (Delshad et al. 1996) is an example of a simulator
that has been used for this purpose. However, because UTCHEM is an Implicit
Pressure and Explicit Concentration (IMPEC) formulation and in its current form
cannot run on parallel computers, realistic surfactant/polymer flooding
simulations are limited to around 100,000 gridblocks because of small timestep
restrictions and insufficient memory.
Recently, the appropriate chemical module was added to the fully implicit,
parallel, EOS compositional simulator called GPAS (General Purpose Adaptive
Simulator) based on a hybrid approach (John et al. 2005). GPAS uses a cubic
equation of state model for the hydrocarbon phase behavior and the parallel and
object-based Fortran 95 framework for managing memory, input/output, and the
necessary communication between processors (Wang et al. 1999; Parashar et al.
1997). In the hybrid approach implemented in GPAS, the material balance
equations for hydrocarbon and water components are solved implicitly first.
Then, the material balance equations for the aqueous components such as
surfactant, polymer, and electrolytes are solved explicitly using the updated
phase fluxes, saturations, and densities.
© 2007. Society of Petroleum Engineers
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History
- Original manuscript received:
24 July 2005
- Meeting paper published:
9 October 2005
- Revised manuscript received:
3 November 2006
- Manuscript approved:
11 December 2006
- Version of record:
20 September 2007
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