Integrated Reservoir-Network Simulation Improves Modeling and Selection of Subsea Boosting Systems for a Deepwater Development

In this paper we present the results and analyses from an integrated simulation study focused on evaluating and selecting subsea boosting systems. The integrated model uses field-management strategies incorporating flowline routing, field and gathering-network constraints, and rate allocation. Novel techniques to model subsea networks enable selection of the boosting system and provide an improved understanding of dynamic conditions encountered in deepwater assets. The selected boosting system ensures safe and reliable operations while improving the project's net present value. Combining responses from reservoir and network systems into an integrated model to evaluate the subsea design requirements is a unique aspect of this study, because this involves novel modeling techniques for boosting systems (pumps). The robust approach ensures consistency of phase behavior across the system components, identification of pump requirements, production optimization, and cost reduction. Analysis of these outputs leads to an improved understanding of field operation strategies, equipment selection and sizing, and production forecasts. The integrated model uses inflow performance relationships (IPRs) from reservoir simulation and vertical lift tables to generate performance curves (PCs), representing well deliverability as a function of tubinghead pressure. Comprehensive field-management logic uses the PCs to determine optimal well operating rates that satisfy all subsurface and surface constraints. This approach reduces a complex set of constraints to a single operating rate. Well operating rate is also a function of the pump power, the pump suction pressure, and the fluid phase behavior across the pumps. The integrated model delivers pump performance within its operating envelope and ensures equipment integrity. Two components of the subsea boosting system, single- and multiphase pumps, drove performance optimization and selection of system operating conditions. The study incorporated a comprehensive analysis of system constraints through implementation of complex field-management rules that accounted for well integrity (completions), performance of network equipment (valves, boosters, pump power requirements), facility capacities, and reservoir deliverability. The integrated study identified the different limiting system constraints throughout the life of the field and improved the overall efficiency of the gathering system. Use of PCs to reduce the constraints to a single operating rate provides tremendous computational performance improvement. Moreover, unlike typical optimization problems, adding more constraints to the system did not affect computational performance significantly.