Challenges of Parametric Uncertainty and Sparse Well Samples for Realistic Modeling of Naturally Fractured Reservoirs: Insights From Discrete Fracture Network Modeling in the Horn River Basin

Komaromi, Bram (University of Calgary) | Bearinger, Doug (Nexen Energy ULC) | Hillier, Chelsey (Nexen Energy ULC)

OnePetro 

However, successful hydraulic stimulation treatments can be challenging to implement, and require considerable forethought. Compositional variation, rock fabric, geomechanical stratigraphy, and natural fracture systems all interact to influence and complicate hydraulic fracture treatments in shale reservoirs (Gale et al., 2006; Passey et al., 2010). Previously published work has highlighted the interaction between natural and induced fractures in the Horn River Basin (Dunphy and Campagna, 2011). This indicates that effective well completions require the efficient utilization of natural fracture systems to enhance permeability and drainage volume. Since natural fracture systems are a significant factor controlling the response of shale reservoirs to hydraulic fracturing, it is essential to identify and understand the key parameters of natural fracture networks that influence the effectiveness of hydraulic fracturing treatments. This paper combines results from natural fracture network characterization with discrete fracture network (DFN) modelling to identify the key parameters that influence hydraulic fracture geometry in the Horn River Basin.

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  Geologic Time: Phanerozoic > Paleozoic > Devonian (0.71)
  Industry: Energy > Oil & Gas > Upstream (1.00)
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