Abstract
Material nonlinearity; boundary and arching constraints; non-uniform reservoir flows; sliding along material interfaces or faults are among the causes of shear deformation or changes in the total stresses, and the resulting stress redistribution in hydrocarbon reservoirs. Previous studies have demonstrated that shear or non-uniform deformation and stress re-distribution in subsurface formations may have significant effects on reservoir fluid flows. Thus, a two-way coupled analysis is the required approach under circumstances where the shear deformation or changes in total stresses in the reservoir cannot be neglected.
A novel coupled multiphysics simulator is developed for the dynamic modeling of multiphase thermal-compositional flow, and elastoplastic geomechanical deformation. The equations that govern multiphase flow in permeable media, heat transport, and elastoplastic geomechanics altogether lead to a highly nonlinear system. Finite-volume and Galerkin finite-element methods are respectively used for the numerical solution of thermal-compositional multiphase fluid-flow and geomechanics equations on general hexahedral (cornerpoint) grids. Due its improved stability and rapid convergence characteristics, the resulting multiphysics system of equations is solved via a fully-implicit formulation using an effective implementation of the Newton-Raphson method in the default mode.
The coupled simulator is by-design maximally modular: The flow simulation and elastoplastic geomechanics modules can be run independently in the single-physics mode. Alternatively, these two fundamental modules can be operated in a two-way coupled mode with explicit, iterative, and fully-implicit coupling options. The coupled modeling system lends itself naturally not only to near-wellbore coupled flow and geomechanical deformation problems where poroplasticity may play a more prominent role but also to reservoir-scale simulations where both poroelasticity and poroplasticity are of relevance. The coupled simulator is validated against analytical solutions for simple cases, and using published data in the open literature. Validation results demonstrate the robust, fast, and accurate predictive capabilities of the multiphysics modeling protocol.
