Robust Nonlinear Newton Solver With Adaptive Interface-Localized Trust Regions
- Øystein S. Klemetsdal (Norwegian University of Science and Technology) | Olav Møyner (Norwegian University of Science and Technology) | Knut-Andreas Lie (SINTEF Digital)
- Document ID
- Society of Petroleum Engineers
- SPE Journal
- Publication Date
- August 2019
- Document Type
- Journal Paper
- 1,576 - 1,594
- 2019.Society of Petroleum Engineers
- Newton's method, flux function, multiphase flow, trust region, transport solver
- 31 in the last 30 days
- 87 since 2007
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The interplay of multiphase-flow effects and pressure/volume/temperature behavior encountered in reservoir simulations often provides strongly coupled nonlinear systems that are challenging to solve numerically. In a sequentially implicit method, many of the essential nonlinearities are associated with the transport equation, and convergence failure for the Newton solver is often caused by steps that pass inflection points and discontinuities in the fractional-flow functions. The industry-standard approach is to heuristically chop timesteps and/or dampen updates suggested by the Newton solver if these exceed a predefined limit. Alternatively, one can use trust regions (TRs) to determine safe updates that stay within regions that have the same curvature for numerical flux. This approach has previously been shown to give unconditional convergence for polymer- and waterflooding problems, also when property curves have kinks or near-discontinuous behavior. Although unconditionally convergent, this method tends to be overly restrictive. Herein, we show how the detection of oscillations in the Newton updates can be used to adaptively switch on and off TRs, resulting in a less-restrictive method better suited for realistic reservoir simulations. We demonstrate the performance of the method for a series of challenging test cases ranging from conceptual 2D setups to realistic (and publicly available) geomodels such as the Norne Field and the recent Olympus model from the Integrated Systems Approach for Petroleum Production (ISAPP) optimization challenge.
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