Improved field management for monitoring, estimating zone productivity/injectivity, and controlling wells with intelligent completions can broaden application of advanced well designs. We have developed a coupled Simulation-Surface Network modeling workflow to evaluate the potential benefit of intelligent injection profile control with a focus on reactive vs proactive control for Gulf of Mexico (GOM) Deepwater Enhanced Oil Recovery (EOR) schemes. The developed injection control solution can be consistently applied to gas, water injection, and gas followed by water injection, to evaluate relative impacts of intelligent injectors on each option. We did this by defining rules for both proactive and reactive injection ICV controls for a GOM Deepwater Wilcox multilayered reservoir. Proactive controls, based on reservoir zone characteristics, pore volume injected, and recoverable pore volume, are dependent on a static reservoir model realization. Proactive control results demonstrate a diminishing return as we begin to observe fluid breakthroughs that results in part from the inevitable uncertainty of the original static assessment so there should be a benefit in reassessing optimal pore volume injection based on reservoir model updates. Reactive control strategies based on measured production response is a challenge in terms of linking injection control events to production responses that are time-lagged and incomplete for understanding gas and water breakthrough. The integrated model captures the effects of topside facilities, risers, flowlines, pressure/temperature at manifolds and topside, seafloor booster pump performance, wellheads, and wellbore to reservoir interactions and ICV controls to provide a realistic evaluation of achievable development alternatives outcomes.
Abstract. Data aggregation services compose, transform, and analyze data from a variety of sources such as simulators, real-time sensor feeds, etc. This paper proposes a methodology for accelerating the development and deployment of data aggregation modules in a service-oriented architecture. Our framework allows existing semantic web-service techniques to be embedded into a programming language thereby leveraging ease of use and flexibility enabled by the former with the expressiveness and tool support of the latter. In our framework data aggregations are written as regular Java programs where the data inputs to the aggregations are specified as predicates over a rich ontology. Our middleware matches these data specifications to the appropriate webservice, automatically invokes it, and performs the required data serializationdeserialization. Finally the data aggregation program is deployed as yet another web-service. Thus, our programming framework hides the complexity of webservice development from the end-user.We discuss the design and implementation of the framework based on open standards, and using state-ofart tools.
This manuscript presents 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 flow-line routing, field and gathering network constraints and rate allocation. Novel techniques to model subsea networks enable the selection of the boosting system and provide an improved understanding of dynamic conditions encountered in deep water 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, as 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 (IPR) from reservoir simulation and vertical lift tables to generate Performance Curves (PC), representing well deliverability as a function of Tubing Head 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 into a single operating rate. Well operating rate, is also a function of pump power, 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 multi-phase 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 into 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.
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