Overview
What this challenge is about.
Implement MPFA-O discretization for pressure on a tetrahedral mesh with explicit fault transmissibility (Aavatsmark et al. 2002 formulation). Couple to a temperature equation via operator splitting (IMPES). Solve nonlinear coupling with Newton-Krylov using JFNK (Jacobian-Free Newton-Krylov) and a physics-based block preconditioner. Validate against 6 historical wellhead datasets (90-day production windows). Report calibrated relative error per dataset (target: under 8 percent), iteration counts, and runtime per 90-day sim. Deliver Python + NumPy/SciPy reference, validation report, and methodology memo.
The Brief
What you'll do, and what you'll demonstrate.
Cut reservoir-pressure forecasting error from 18 percent to under 8 percent over a 90-day window by improving the PDE discretization and nonlinear solver.
Earning criteria — what you'll demonstrate
- Implement MPFA-O for anisotropic flux on unstructured meshes
- Couple pressure and temperature via operator-splitting (IMPES)
- Apply Jacobian-Free Newton-Krylov with physics-based preconditioning
- Validate a PDE solver against historical industrial data with calibrated uncertainty
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Skills
Skills you'll demonstrate.
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Careers
Roles this prepares you for.
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