- peter.schultzendorff@uib.no
- Visitor address
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Christies gate 12
5015 Bergen - Postal address
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P.O. Box 7803NO-5020 BergenNorway
Research groups
Research
I am a PhD student at the Centre for Sustainable Subsurface Resources (CSSR), which researches technologies that enable the transition of the Norwegian continental shelf to a sustainable future. My field of research is the coupling of classical physics-based models for reservoir simulations with new data-driven methods. The goal is to combine the best of both worlds to enable high fidelity to physics and data, as well as fast computation for reservoir simulations. My work focuses on the mathematical analysis of such coupled problem and the development of robust and stable solvers. This work is motivated by applications such as CO2 storage, H2 storage, and renewable-powered offshore operations. As part of my research, I contribute to the development of the open-source simulator PorePy and the pyopmnearwell framework for the simulator OPM Flow.
Publications
Poster
- Schultzendorff, Peter Moritz von; Both, Jakub Wiktor; Nordbotten, Jan Martin et al. (2025). An adaptive homotopy continuation solver for incompressible two-phase flow in porous media. (external link)
- Schultzendorff, Peter Moritz von; Both, Jakub Wiktor; Nordbotten, Jan Martin et al. (2025). An adaptive homotopy continuation solver for incompressible two-phase flow in porous media. (external link)
- Kane, Birane; Schultzendorff, Peter Moritz von; Sandve, Tor Harald (2025). Machine Learning integration into a reservoir simulatorMachine Learning integration into a reservoir simulator. (external link)
- Schultzendorff, Peter Moritz von; Nordbotten, Jan Martin; Sandve, Tor Harald et al. (2025). An adaptive homotopy continuation solver for incompressible two-phase flow in porous media. (external link)
- Schultzendorff, Peter Moritz von; Sandve, Tor Harald; Kane, Birane et al. (2024). A machine-learned near-well model in OPM Flow. (external link)
- Schultzendorff, Peter Moritz von; Both, Jakub Wiktor; Nordbotten, Jan Martin et al. (2023). A machine learned near-well model in OPM. (external link)
Academic lecture
- Schultzendorff, Peter Moritz von; Both, Jakub Wiktor; Nordbotten, Jan Martin et al. (2025). An adaptive homotopy continuation solver for incompressible two-phase flow in porous media. (external link)
- Schultzendorff, Peter Moritz von; Both, Jakub Wiktor; Nordbotten, Jan Martin et al. (2025). An adaptive homotopy continuation solver for incompressible two-phase flow in porous media. (external link)
- Schultzendorff, Peter Moritz von; Vohralík, Martin; Both, Jakub Wiktor et al. (2025). Adaptive homotopy continuation for machine-learned relative permeability models in porous media flow. (external link)
- Schultzendorff, Peter Moritz von; Sandve, Tor Harald; Kane, Birane et al. (2024). A machine learned near-well model in OPM. (external link)
- Schultzendorff, Peter Moritz von; Sandve, Tor Harald; Kane, Birane et al. (2024). A machine-learned near-well model in OPM Flow. (external link)
- Schultzendorff, Peter Moritz von; Both, Jakub Wiktor; Nordbotten, Jan Martin et al. (2023). A machine learned near-well model in OPM. (external link)
- Schultzendorff, Peter Moritz von; Both, Jakub Wiktor; Nordbotten, Jan Martin et al. (2023). Homotopy continuation for a two-phase flow model with machine-learned relative permeabilities. (external link)