Abstract
In this work, we implement new software for improved waterflood management by combining classical finite volume reservoir simulation together with streamline tracing and corresponding interwell flux evaluations to optimize waterflood performance. We have introduced two basic modules here: a commercial reservoir simulator and our own streamline tracing and waterflood management program. Waterflood simulation is performed for a certain time span until simulation is paused, and the streamline tracing program is called to calculate interwell fluxes and adjust new well rates for better waterflood performance. The simulation continues afterwards until the next tracing and adjustment point is reached. The two modules work iteratively. The streamline tracing program is designed to trace streamlines on a compressible velocity field and a general corner point grid system with nonneighboring connections. The new injection rates are adjusted according to each well′s injection efficiency calculated from interwell multi‐phase fluxes. Streamline tracing is performed successfully not only on simple geometry corner point grid cases, but also on heavily faulted realistic reservoirs under waterflood. After readjusting injection rates multiple times during the simulation, we typically observe a reduction in field water cut of up to 5% and an increase in oil recovery in our test cases. Interwell flux information serves as effective diagnostic tools to identify injector‐producer pairs with large amount of water cycling. All simulations conducted here are rigorously finite volume based, which takes into account the full physics of nonadvective processes such as gravity and capillary effects. In conclusion, we have implemented a streamline‐based waterflood management program which works iteratively and cooperatively with a commercial reservoir simulator, without switching to streamline simulation. It provides an effective solution for improving oil recovery in brown fields by combining the rigorous mathematical nature of finite volume simulation and the power of streamline‐based flood management.
Highlights
Streamline simulation, which is effective in solving large, geologically complex and heterogeneous subsurface porous media flow problems, serves as an effective and complementary technology to traditional Eulerian finite volume-based simulation [1]
We introduce a novel software implementation, which uses the multiphase velocity field from a classical finite volume reservoir simulator for streamline tracing and interwell flux calculations. e flood efficiencies of each injector/producer pair are used to further determine the future injection/production rates of each well in order to achieve improved waterflood performance
We show improved oil recovery and waterflood management by combing the advantages of streamline-based flux information to optimize waterflood and the more rigorous and general purpose nature of finite volume simulation
Summary
Streamline simulation, which is effective in solving large, geologically complex and heterogeneous subsurface porous media flow problems, serves as an effective and complementary technology to traditional Eulerian finite volume-based simulation [1]. By calculating interwell multiphase fluxes using streamlines connecting between injectors and producers, streamline simulation can identify how much oil production comes from the pressure support from a certain injector, which quantitatively generates the waterflood efficiency of each injector/producer pair With this important information, adjustment of injection/production rates can be made, with the goal of reducing water cycling, increasing oil recovery and improving flood management [15, 16]. Erefore, there is a need to combine the merits and power of streamline-based interwell connectivity and waterflood management, together with the wider applicable range and rigorous mathematical treatment of nonadvective forces, compressibility, and frequently changing well controls in classical finite volume reservoir simulation. We show improved oil recovery and waterflood management by combing the advantages of streamline-based flux information to optimize waterflood and the more rigorous and general purpose nature of finite volume simulation
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