History Matching Using Hybrid Parameterisation and Optimisation Methods

Abstract

Reservoir models are commonly used in the oil and gas industry to predict the reservoir behaviour and forecasted production. Conditioning reservoir models to dynamic production data is known as history matching, which is usually carried out to enhance the predicted reservoir performance. Uncertainty quantification is also an important aspect, and encompasses identifying multiple history matched models, constrained to a geological concept. History matching and uncertainty quantification can be accomplished by identifying and utilising efficient and speedy optimisation techniques. The assisted history matching process usually includes two processes; the first is parameterisation which consists of reducing the number of matching parameters, in order to avoid adjusting too many parameters with respect to the amount of production data available. Any overparameterisation would lead to an ill posed formulation of the inverse problem. The second process involves optimisation which aims to reduce a misfit or objective function and the success of this stage is greatly dependent on the previous one.