WP 3: Optimisation and data assimilation

1. Introduction

We aim at extending optimization of facilities powered by gas turbines (with fixed energy cost), to include multi-source energy resources, including offshore wind, locally stored hydrogen, land-based electricity via cables, gas turbines with alternative fuels, and/or batteries. We focus on strategies that combine multi-source energy over daily and seasonal variatins with multiple constraints relevant for electrification, such as balanced energy storage and usage, constraints from the grid during peak demand, and constraints from the facilities.

2. Research goals

The goal of WP3 is to build fast and robust algorithms that enable continuous optimization and prediction, a feature that will become increasingly required of reservoir management workflows in the move to renewable-powered operations. As such, we seek to solve the challenges and explore opportunities by a step-change towards efficient optimization that accounts for rapid fluctuations in price and availability of energy. 

3. Delivery

Deliverables in the form of open-source software or algorithms:

  • Optimization component easily integrated into a closed-loop workflow
  • Robust and user-friendly configuration for typical NCS fields
  • Improved history-matching workflow for proxy models combined with machine learning

WP3 lead

Rolf J. Lorentzen
Senior Researcher
Energy & Technology Department, NORCE


3.1 Formulate the optimisation problem for renewable powered hydrocarbon production

3.2 Improving performance and robustness of reservoir management workflows

WP3 staff

Andreas Stordal
Kjersti Solberg Eikrem (WP Deputy)