Remedy
In 2020, the petroleum activity on the Norwegian Continental Shelf (NCS) emitted an estimated 12.5 million tons of CO2 equivalents, and NCS 84.7% of the emissions originated from energy production using gas turbines. A substantial part of the energy use is related to drilling wells and injecting water. Hence, we can significantly reduce greenhouse-gas emissions from the petroleum industry by reducing energy use during field development and production. The REMEDY workflow applies state-of-the-art ensemble methods for history matching, optimization, and decision making to determine the optimal drilling schedules and production strategies that minimize greenhouse gas emissions and energy usage while maximizing oil recovery.
For reaching the climate targets for 2030 and 2050, the industry is in pressing need of extending its decision management tools to include emission reduction. REMEDY will build on the potential of ensemble methods to develop the methodologies needed for such a comprehensive workflow in less than four years, and significantly, and fast, reducing the future greenhouse-gas emissions on the NCS, contributing to reaching the new climate targets for 2030 and 2050. REMEDY will deliver workflows and algorithms ready for implementation and use by the industry partners during and following the project.
Publications and outreach
Only lists those co-authored by our members:-
Conf-paper by: Stordal, A.S. , Lorentzen, R.J. (2025)
Comparing three different methods for production optimization
EAGE Annual 2025
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Paper by: Oliver, D. (2024)
Robust Optimization Using the Mean Model with Bias Correction
Mathematical Geosciences
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Conf-paper by: Evensen, G. (2024)
Iterative ensemble smoothers for data assimilation
Summer School: Data Assimilation for Geosciences
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Paper by: Evensen, G. , Vossepoel, F.C., Leeuwen, P.J.V. (2024)
Iterative Ensemble Smoothers for Data Assimilation in Coupled Nonlinear Multiscale Models
Monthly Weather Review
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Conf-paper by: Evensen, G. (2024)
On the formulation of the ensemble history-matching problem
PAUQ: International Workshop : Practical Data Assimilation and Uncertainty Quantification
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Conf-paper by: Oliver, D. (2023)
Hybrid IES data assimilation
Foundations of Computational Mathematics
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Conf-paper by: Oliver, D. (2023)
Uncertainty quantification for subsurface petroleum reservoirs
PEST Conference - The Path from Data to Decisions
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Conf-paper by: Evensen, G. (2023)
Learnings from petroleum reservoir history matching
ISDA 2023: International Symposium on Data Assimilation
Total: 8