The offshore production of oil and gas is a complex process where a lot of decisions have to be taken to meet the goals in the short, medium and long run, ranging from planning and asset management to small corrective actions. Decisions that have to be taken on decision horizon ranging from a few hours to days is typically known as Daily Production Optimization which is crucial during the entire production phase of the field to maximise the revenue. Daily production optimization generally seeks to maximise the oil and gas production and reduce the cost of production by choosing the production target for each well, allocation of resources among the wells such as the available gas lift, power etc.

As the era of easy oil is declining, the volume and the complexity of oil and gas operations is ever increasing. Oil wells producing from challenging reservoirs with heavy viscous crude, wells with advanced completions and complex subsea tie-backs and subsea processing causes decision-making and planning a challenging task. Software tools such as PROSPER and GAP are widely used in the upstream oil and gas industry to do this. These software tools solve nonlinear optimisation problems based on steady state well models that are developed using first principles and correlations and are updated at irregular intervals. However, in reality, the system is subject to wide range of uncertainties that are not taken into account in such offline software tools used for production optimisation.

The most common approach is to solve what is known as the deterministic problem with nominal models, where all the uncertain parameters are assumed to take their expected value. The quality of the optimal solution is heavily affected when data and model uncertainty are disregarded. The main focus of this sub-project is to investigate and develop optimization methods that explicitly takes the uncertainty into account and assists optimal decision making in the face of uncertainty.