The objective of this study is to develop a workflow to rapidly simulate injection and production phases of hydraulically fractured shale wells by (a) incorporating fracture propagation in flow simulators using a simplified physical model for pressure-dependent fracture conductivity and fracture pore volume (b) developing a hybrid Fast Marching Method (FMM) and 3D Finite Difference(FD) model for efficient coupled simulation and (c) automating the entire workflow for rapid analysis in a single simulator domain.

Pressure-dependent fracture transmissibility and pore volume multiplier models are assigned to predefined potential hydraulic fracture paths to mimic geomechanical behavior of fractures (i.e. opening and closure). The multipliers are based on empirical equations (e.g., Barton-Bandis model) and theoretical models (e.g., linear elastic fracture mechanics and cubic law). The FMM-based simulation transforms an original 3D reservoir model into an equivalent 1D simulation grid leading to orders of magnitude faster computation and is utilized to efficiently history-match field production and pressure data. A population-based history matching algorithm was used to minimize data misfit and quantify uncertainties in tuning parameters.

We demonstrate the effectiveness and efficiency of the proposed method using synthetic and field examples. First, we validated our proposed simplified fracture propagation model with a comprehensive coupled fluid flow and geomechanical simulator, ABAQUS. The results showed close agreement in both injection pressure response and fracture geometry. Next, the method was applied to a field case to history-match injection pressure and production data. Fracture geometry and properties were inferred from the injection phase and are input to the production phase modeling. After history matching, the misfit and uncertainty ranges in reservoir and fracture properties were substantially reduced.

The proposed workflow enables rapid analyses of hydraulically fractured wells and does not require computationally demanding geomechanical simulations to generate fracture geometry and properties. The FMM-based simulation further improves computational efficiency and allows us to automate the workflow using population-based history matching algorithms to quantify and assess parameter uncertainty.

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