Thermal Streamline Simulation for Hot Water Flooding
- Zhouyuan Zhu (Stanford University) | Margot Geertrui Gerritsen (Stanford University) | Marco Roberto Thiele (Streamsim Technologies, Inc.)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Simulation Symposium, 2-4 February, The Woodlands, Texas
- Publication Date
- Document Type
- Conference Paper
- 2009. Society of Petroleum Engineers
- 5.5 Reservoir Simulation, 5.5.8 History Matching, 7.4.4 Energy Policy and Regulation, 4.3.4 Scale, 5.3.9 Steam Assisted Gravity Drainage, 5.4.2 Gas Injection Methods, 5.2.1 Phase Behavior and PVT Measurements, 5.4.6 Thermal Methods, 5.5.7 Streamline Simulation, 5.3.1 Flow in Porous Media, 5.4.1 Waterflooding
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We explore the extension of streamline simulation (SL) to thermal recovery processes. For each global time step of the thermal streamline simulator, we first compute the pressure field on an Eulerian grid. We then solve for the advective parts of the mass balance and energy equations along individual streamlines. At the end of each global time step, we account for the nonadvective terms of the mass balance and energy equations on the Eulerian grid along with gravity. We included temperature dependent viscosity and account for thermal expansion. We tested the thermal streamline simulator on two-dimensional heterogeneous quarter five spot problems and compared the results with those computed by a commercial thermal simulator on both accuracy and efficiency. Sensitivity studies for compressibility, gravity and thermal conduction effects are presented. The thermal streamline simulator is capable of producing accurate results at a computational cost that is much lower than that of existing Eulerian simulators.
Thermal enhanced recovery technique account for over 60% of the U.S. Enhanced Oil Recovery (EOR) production. Steam flooding and hot water flooding are most widely used, but other processes, such as in-situ combustion and steam-assisted gravity drainage are applied and are especially attractive for unlocking heavy oil resources.
Planning and management of these processes generally make extensive use of thermal reservoir simulations. Nearly all commercial and academic thermal simulators are traditional finite volume based codes that use either a fully implicit (FIM) time stepping method or an adaptive implicit method for stabililty (Aziz and Settari, 1979). The computational cost of thermal processes is very high because of the strongly nonlinear flow, and as a result, the computational costs are prohibitively high when running optimization and/or sensitivity studies on grids with desirable numerical resolution. There is therefore an urgent need for fast approximate solvers for thermal problems. The essence of this work is to explore the extension of streamline simulation to thermal enhanced recovery processes. Our aim is to design a fast and effective simulator that gives sufficient accuracy for use in reservoir simulation studies, such as well placement optimization and history matching.
|File Size||1 MB||Number of Pages||14|