Abstract

Abstract A new approach that combines the use of continuum and discrete fracture modeling methods has been developed. The approach provides the unique opportunity to constrain the fractured models to all existing geologic, geophysical, and engineering data, and hence derive conditioned discrete fracture models. Such models exhibit greater reality, since the spatial distribution of fractures reflects the underlying drivers that control fracture creation and growth. The modeling process is initiated by constructing continuous fracture models that are able to capture the underlying complex relationships that may exist between fracture intensity (defined by static measures, such as fracture count, or dynamic measures, such as hydrocarbon production), and many possible geologic drivers (e.g. structure, thickness, lithology, faults, porosity). Artificial intelligence tools are used to correlate the multitude of geologic drivers with the chosen measure of fracture intensity. The resulting continuous fracture intensity models are then passed to a discrete fracture network (DFN) method. The current practice in DFN modeling is to assume fractures are spatially distributed according to a stationary Poisson process, simple clustering rules, or controlled by a single geologic driver. All these approaches will in general be overly simplistic and lead to unreliable predictions of fracture distribution away from well locations. In contrast, the new approach determines the number of fractures in each grid-block, based on the value of the fracture intensity provided by the continuous model. As a result, the discrete fracture models honor all the geologic conditions reflected in the continuous models and exhibit all the observed fracture features. The conditioned DFN models are used to build a realistic and detailed model of flow in discrete conduits. There are two main areas where detailed discrete fracture models can be used: (1) Upscaling of fracture properties (permeability, porosity and σ factor) for input into reservoir simulators; and (2) Optimization of well-design, completion and operation based on an understanding of the inter-well scale flows. For accurate results, the full permeability tensor is calculated for each grid-block based on flow calculations using generalized linear boundary conditions. Inter-well flows are analyzed in terms of the variability in flow paths, characterized by distance and time traveled, through the fracture network connecting injectors and producers.

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