Within the framework of reservoir management streamline simulation finds one of its typical applications as one of the effective tool to improve gasflood and pressure maintance performance. Streamlines provide an instantaneous visualization of flow patterns as a function of reservoir heterogeneity. Additionally they also provide an estimation of the well allocation factors (WAFs) between injection and producing wells. Such information is a default outcome from streamline models but not from finite difference simulation and it is particularly useful in optimizing and balancing well patterns and field scale injection rates. However finite difference simulation has the advantage of implicitly taking into account all the details of an existing simulation model, especially advanced well management strategy. In this paper we demonstrate a straightforward workflow for optimizing injection rate based on a comprehensive analysis of two key parameters: injector efficiency (IE) metric and WAFs. The optimization approach consists of a three step procedure starting with streamline analysis using commercial software which combines the power of finite difference simulators and streamline technology to derive streamlines from the flux field generated by the finite difference simulation that represent a snapshot of the flow pattern within the reservoir, well drainage region information and fluid allocation changes with the flood progression. Second using a simple analytical calculation to compute weighting factors for injection/production rate targets from a derived ranking of the wells (IE). Finally reallocation of injected fluid volumes from low-efficiency to high-efficiency injectors improves volumetric displacement and sweep efficiency in the less swept areas of the reservoir. The application of this workflow is demonstrated with a real-field example of an onshore tight sandstone reservoir where the pattern balancing has led to incremental production of 3.5 % over the 5 year forecast in which the IE average of the field is the benchmark for whether more or less injection volumes were required while obeying facility constraints.

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