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Real-time decision making by production engineers in a petroleum field can be very challenging, especially when multiple wells with diverse operating conditions and production behaviours are present. Hence, semi-analytic or heuristic procedures are unlikely to yield an optimal operating strategy. This paper implements a Real-Time Production Optimisation (RTPO) approach to maximising production from naturally flowing, gas-lifted and Electrical Submersible Pump (ESP)-assisted wells while satisfying multiple operational constraints. This is achieved via the application of reduced order models which are developed by querying a black box production network simulator multiple times using different inputs. Also exploited in this work is the inherent decomposable property of the production network, into smaller components (wells, valves pipelines and separators), such that mass balance equations comprise the algebraic constraints of the optimisation framework which is solved as an MINLP. The adopted formulation also offers the advantage of flexibility for problem adjustment under different practical operating conditions which are presented as case studies. The changes incorporated into the production system include: increased liquid handling capacity of downstream separators, decreased well productivity/increased water cut and well intervention problems. The ability of the adopted framework to provide accurate and speedy computations of the optimal production scenario makes it reliable for real-time decision support.
- Real Time Production Optimisation (RTPO)
- Mixed Integer Nonlinear Programming (MINLP)
- Well routing
- Electrical Submersible Pumps (ESP)
- Gas Lift (GL)
- Naturally flowing (NF)
- Gas Oil Ratio (GOR)
- Water Cut (WC)
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- 1 Finished
1/09/17 → 31/10/18