Automated methodologies for decision support in field development

PhD Candidate Guowen Lei

Main Supervisor Milan Stanko

Sponsor: Lundin Energy Norway AS

The aim of this project is to develop computer-based robust and reproducible methodologies that advise field planners in defining the main features of the field in phases DG0-DG2. This will be performed by:
1) developing a digital twin of the field’s value chain
2) developing machine-learning based models and integrating models of various nature and complexity
3) developing and testing methodologies (e.g. optimization, probabilistic simulations) to determine optimum design features
4) analyzing uncertainty and energy usage, CO2 emissions, ease of decommissioning.

Project result: Efficient formulation to find optimal production strategies matches reality
Two study cases showing that efficient optimization can provide valuable insights to field planning and matches reality