The key to successful application of surrogate modelling is the ability to quickly generate high quality data over a large parameter space. This can be achieved through application of Variable Fidelity Modelling (VFM), which is a data fusion technique that allows data from different sources to be combined. VFM can be used to correct a dataset obtained by a simple and fast method with a small number of high quality samples in order to generate a high-fidelity surrogate at a marginal cost.