A multi-objective optimisation model to reduce greenhouse gas emissions and costs in offshore natural gas upstream chains

Abstract

The urgency of climate change, while the world economy is projected to depend on fossil fuels for some time, requires substantial reduction of greenhouse gas emissions in the oil and gas industry. This study proposes a methodology for the decarbonisation of offshore natural gas production networks through progressive electrification, either by connecting offshore platforms with nearby renewable energy sources, e.g. offshore wind farms, or by sharing resources so as to improve their energy generation efficiency. In this context, a novel multi-objective mixed-integer linear programming model is proposed to simultaneously minimise greenhouse gas emissions and associated costs from a determined offshore platform network, considering technical constraints, such as maintaining the energy balance of the network, ensuring that cables are installed to enable energy flows, and respecting the maximum generation capacities and minimum operating loads of turbines. For demonstration purposes, the proposed methodology was applied to a UK Southern North Sea network and optimised using the augmented -constraint method. The Pareto front approximation obtained suggests that the studied network’s cumulative greenhouse gas emissions can be reduced by 25% over the next 10 years at an average cost of US$370.9 per tonne CO2e. This study also explores the impact that uncertainties and postponing investment decisions may have in the set context.