Improving Pipeline Flow Modeling by Multivariate Analysis

Reliable operation and monitoring of subsea pipelines rely on accurate modelling of the flow as well as good measurements. While one-dimensional pipeline models have been made highly accurate they make use of simplifications and are dependent on an accurate description of the surroundings. For a subsea pipeline the degree of burial can vary, the exact properties of the soil may be lacking for parts of the pipeline, and one typically has to rely on an oceanographic model for the ambient temperature. Uncertainties in the input reduce the accuracy of the modelling, however information of the inaccuracies of the model can be obtained by analyzing the historical differences between modelled and measured parameters. This paper makes use of multivariate analysis to analyze the inaccuracies of a onedimensional flow model and shows how it can be used to improve the predictive power of the flow model.