Loading…
This event has ended. View the official site or create your own event → Check it out
This event has ended. Create your own
View analytic
Thursday, March 16 • 4:00pm - 5:30pm
Poster: Parallelization for Coupled Fluid-Heat Flow and Poroelastoplastic Geomechanics Simulation

Sign up or log in to save this to your schedule and see who's attending!

Feedback form is now closed.
In coupled method for flow and geomechanics simulation, the computational cost becomes very large as gridblock number increases. The flow problem and the geomechanics problem are separately solved and then iteratively coupled so that the interaction between flow in porous media and the rock deformation can be captured. In order to obtain fast simulation, in this work, a parallel solver is implemented in the coupled simulation to speedup solving of matrices. Parallel array assembly is also introduced so that array values can be efficiently assigned in very large linear systems.
The parallelization is based on a serial sequentially coupled non-isothermal fluid flow and elastoplastic geomechanics simulator. MPI-based parallel array assembly and the parallel solver PETSc are first implemented to the flow and geomechanics problems separately. Specifically, the parallel array assembly is for the sparse format of the Jacobian matrices, while the PETSc solver is introduced to replace the original serial solver. The solver is GMRES based on block Jacobi preconditioner. Then the two parts are sequentially coupled together. Different matrix decomposition methods are tested to understand its impact on solver time and solver iteration numbers. The reservoir model in this work has one million cells.
Results indicate that the parallel solver improves the linear system solving efficiency in both flow and geomechanics problems. Scalability is also observed in the parallel array assembly in both problems. In general, the speedup is better achieved in the geomechanics problem than in the flow problem. After the two parallelized problems are sequentially coupled together, the overall scalability of the coupled model is still honored. The optimum overall speedup for the coupled method reaches 14. It is observed that plasticity computation in the geomechanics problem results in load imbalance, as plasticity only occurs at certain gridblocks where the rock failure yield condition is triggered. Also, different matrix decomposition methods lead to different matrix solving time and different solver iteration numbers to convergence. This work can be straightforwardly applied to serial sequentially coupled models considering various fluid flow and rock deformation physics to obtain practical speedup in MPI-based environment.


Thursday March 16, 2017 4:00pm - 5:30pm
Exhibit Hall BRC