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Technical Paper: Modeling from Reservoir to Export: A Compositional Approach for Integrated Asset Model of Different Gas Fields in North Kuwait Jurassic Carbonate Reservoirs

Society: SPE
Paper Number: 173308
Presentation Date: 2015
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Abstract

A project was undertaken to construct an overview to build an integrated asset model (IAM) of an onshore fractured carbonate gas condensate and volatile oil asset in Northern Kuwait that is considered the first gas asset discovered in Kuwait. The asset has the potential to produce from six distributed fields producing from four hydrocarbon-bearing structures. The development strategy calls for extensive drilling and facilities expansion to increase and sustain production with the potential addition of depletion compression to further sustain the plateau. Because the reservoirs are highly compartmentalized, they are split into 19 separate models. Production is through three surface facilities, fluids vary significantly across the field from sour gas condensate to volatile oil, and it is important to consider the impact of reservoir deliverability, facilities capacity, and surface backpressure when evaluating different development scenarios. 

A novel IAM was constructed that integrates reservoirs, wells, pipelines, and facilities models into an integration platform. The IAM comprises 19 black oil dual porosity reservoir models coupled to a compositional network model via black oil delumping to convert the subsurface rates into six-components composition. A split table (compositional delumping) is then used to convert the six-components composition to 35 surface components to be used in the equation-of-state (EOS) surface network models to estimate the composition at each point at the surface (inlet and outlet of each facility). Then the network model is coupled to surface facilities modeling to estimate the rates and composition at the export level. This idea of mapping the subsurface fluid from black oil at subsurface to compositional at surface reduces the subsurface running time and makes the IAM more feasible from the running time perspective. 

The IAM has highlighted several differences versus the stand-alone modeling and the coupled modeling at the surface only. First, more accurate accounting for backpressure results in an increase in the plateau. Second, a production forecast for each facility gives a detailed analysis of production and the number of wells for each facility. Finally, detailed compositional information becomes available at all points in the surface network, which is important input to the facilities design.

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