Abstract. Reservoir modeling is playing an increasingly important role in developing and producing hydrocarbon reserves. In this paper, we provide a brief overview of some main challenges in reservoir modeling, i.e., accurate and efficient modeling of complex reservoir geometry and heterogeneous reservoir properties. We then present modeling techniques we recently developed in addressing these challenges, including a method for generating constrained Voronoi grids and a generic global scale-up method. We focus on the Voronoi gridding method, which is based on a new constrained Delaunay triangulation algorithm and a rigorous method of adapting Voronoi grids to piecewise linear constraints. The global scale-up method based on generic flows is briefly described. Numerical examples are provided to demonstrate the techniques and the advantage of combining them in constructing accurate and efficient reservoir models.
An accurate and efficient reservoir modeling process is essential for developing and producing hydrocarbon reserves, especially from unconventional resources. In this paper, we address some of the main challenges associated with modeling complex reservoir geometry and heterogeneous reservoir properties. We present recently developed techniques for adaptively constrained 2.5D Voronoi grid generation and for generic global flow-based scale-up. Our novel gridding approach is based on a new constrained Delaunay triangulation algorithm and a rigorous procedure of constructing a Voronoi grid that conforms to piecewise linear constraints. These gridding approaches allow us to generate 2.5D Voronoi grids that precisely honor small faults, intersections of multiple faults, and intersections of faults at sharp angles, as well as adapt the grid cell sizes to a specified density function. By precisely representing geologic structures in our simulation grid and by accurately scaling up fine-scale geologic properties, we improve the consistency between our geologic descriptions and reservoir simulation models, leading to more accurate simulation results. Numerical examples are provided to demonstrate the techniques and the advantages (both in efficiency and accuracy) of using adaptive gridding with global scale-up. Introduction Reservoir modeling is a crucial step in hydrocarbon resource development and management. It provides a venue for integrating and reconciling geologic concepts and data about a reservoir obtained at different scales. The scale of data ranges from a few inches for core plugs, a few feet for well logs, to many square miles for seismic imagies. Due to monetary and time constraints, directly sampled data of reservoir rock and fluid properties is sparse. Therefore, geologic interpretations based on seismic information and geologic concepts are required to supplement the measured data in order to provide adequate descriptions. A key challenge in reservoir modeling is accurate representation of the reservoir geometry of both the structural framework (i.e., horizons/major depositional surfaces that are nearly horizontal and fault surfaces that can have arbitrary spatial size and orientation) and the detailed stratigraphic layering (Figure 1). The structural framework delineates major compartments of a reservoir and often provides the first order controls on in-place fluid volumes and fluid movement during production. Thus, it is important to model the structural framework accurately. However, despite decades of advances in grid generation across many disciplines, grid generation for practical reservoir modeling and simulation remains a daunting task. For typical reservoir geometries with a high aspect ratio of horizontal to vertical dimensions, 2.5D (prismatic) Voronoi grids, constructed by projection or extrusion of a 2D Voronoi grid in vertical or nearly vertical direction, are a natural choice for reservoir simulations. Prismatic grid cells can easily be constrained to resolve horizons or stratigraphic layer boundaries. Voronoi grids (constructed as a dual to Delaunay triangulations) are much more flexible and adaptive than the corner point grids commonly used in commercial reservoir simulators, generally providing much fewer grid cells for the same accuracy of geometry representation and simulation. They also help reduce the grid orientation effect on numerical solutions of fluid transport problems (Verma 1996). Although less problematic than corner point grids, generating 2.5D Voronoi grids is often very challenging in practice due to the constraints these grids have to honor, which include numerous (intersecting) faults, pinch-outs (cf. Lyons et al. 2006), correlated heterogeneities (e.g., permeability extremes), and adaptive refinement as required for efficient and accurate flow simulations.
Long-term completion performance is important for the economic development of any field. As fields are now developed in environments that are capital intensive and increasingly technically challenging, new technologies are required for optimization of the completion design. Stand-alone reservoir simulators lack the required detail on the completion side, while stand-alone wellbore simulators do not have the long-term reservoir performance information available. Even the new class of coupled wellbore/reservoir simulators often lack comprehensive completion design capabilities. We have developed a fully-coupled black-oil wellbore/reservoir model which accounts for the necessary details for an optimized completion design. Specifically, the model couples ExxonMobil's proprietary reservoir simulator and a detailed completion hydraulics simulator such that the reservoir flow, wellbore tubing and annulus flows, and pressure fields are simulated simultaneously. In this paper, we compare different synthetic cases involving open-holes, pre-drilled liners, packers, and inflow control devices that demonstrate unique completion opportunities captured by using our modeling capabilities. We show that our model provides not only detailed information regarding the tubing and annulus flow and the associated pressure drops along the completion, but also the impact of different completion types on short- and long-term reservoir recovery. Our results show the significance of this new coupled approach in its ability to relate the reservoir performance and the flow dynamics through various completion types.
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