Abstract: A computer-implemented method for predicting hydrocarbon fluid properties comprises the step of receiving an incomplete set of pressure-volume-temperature (PVT) data for hydrocarbon fluid samples from a PVT data base; reading the incomplete set of PVT data; transforming the incomplete set of PVT data into a unified data structure; selecting items of the PVT data from the incomplete set of PVT data; processing the selected items of the PVT data to identify a plurality of correlations in the selected items of the PVT data based on one or more of the fluid properties of the hydrocarbon fluid samples; clustering, using at least one of a plurality of clustering schemes, the selected items of the PVT data into a plurality of clusters; and performing machine learning on the plurality of clusters to predict missing fluid properties in the incomplete set of PVT data to obtain a complete set of PVT data.

Abstract: An integrated capacity modelling system for monitoring and controlling multiple oil and gas assets, the system comprising a data acquisition module, capable of acquiring upstream data, whereas upstream data may include information from the multiple oil and gas assets; a subsurface and surface processes simulation module, capable of simulating production and injection performance of multiple oil and gas assets from the reservoir to the sales delivery point; a data assimilation module, capable of extracting key features in the data for the purposes of calculating production capacity of multiple oil and gas assets from the acquired upstream data and from the simulation module and for building an asset capacity model thereof; a data presentation module, capable of presenting all the components of the asset capacity model of multiple oil and gas assets, wherein the presentation module is capable of presenting the asset capacity model of multiple oil and gas assets in nodes of a hierarchical structure of a pluralit