An Integrated Pore-to-Process Model for the Largest Clastic Oilfield in the World

Author:

Dashti Qasem1,Abdulrazzaq Hanan1,Al-Shammari Nouf1,Al-Habashi Haytham1,Al-Rumaidhi Meshal1,Talabi Oluwole A.2,Franco Francy Milena2,Muhammad Yaser2,Zhang Michael Qiong2,Prakash Roshan2,Goula Masllorens Nicolau2,Ali Samad2

Affiliation:

1. Kuwait Oil Company

2. Schlumberger

Abstract

Abstract This paper discusses the development of full pore-to-process integrated asset models (IAM) for the Greater Burgan (GB) oilfield in Kuwait, the largest clastic oil field in the world. The IAM links the reservoir model with the multiple wells, pipelines, network models and process facilities models for improved forecasting and operational excellence in the South and East Kuwait asset of Kuwait Oil Company. The main objective behind the development of this integrated asset model is to enable enhanced asset management and to improve decision making, accounting for the complex interactions and synergies between reservoirs, production networks and process facilities in the hydrocarbon flow path all the way from the reservoir to the export points. The IAMs were developed using calibrated models built using next-generation simulators that enabled the running of forecast scenarios from the pore to process. The reservoir model was developed using a high-resolution reservoir simulator that enabled the simulation of this giant oilfield with more than 2000 wells in a few hours. The reservoir model was then coupled to the full-physics well-and-network models for 3 gathering centres of key interest which had also been previously calibrated to match wells and manifold rates and pressures. Finally, the network model was connected to the high-performance process facility model at the manifold headers. The reservoir-network coupling was done at the well level, each well coupled at the bottomhole with an updated IPR passed to the network and a resulting outflow constraint passed back to the reservoir every timestep to capture any effects of pressure regime established in the network. The network-process facility connection was established by using a feedforward push of the calculated mass flow rate, pressure, GOR, water cut, and temperature at the manifold, as updated boundary conditions to estimate the quantity and quality of fluids produced from the facility. The results of the integrated models showed moderate impact of the network on the performance of the reservoir over a 5-year forecast. Integration of the vast number of wells and network models with the crude processing facilities in a single IAM platform enables the evaluation of oil production improvement opportunities in terms of their long-term dynamic impact on the reservoir management. The IAM models will help to identify the bottlenecks in the system, optimize the production and achieve the aggressive oil target of the GB asset. This is the first set of fully first operational IAMs for Greater Burgan that includes all three key components – reservoir, network, and process facilities. The IAM gives access to control and define constraints in all the component models, making it an effective tool for further analysing development and optimization strategies for improved asset management of the largest clastic oilfield in the world.

Publisher

SPE

Reference12 articles.

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