Ensemble-based multi-objective optimization of on-off control devices under geological uncertainty

Ensemble-based multi-objective optimization of on-off control devices under geological uncertainty

Fonseca, R.M.
Leeuwenburgh, O.
Rossa, E.D.
van den Hof, P.M.J.
Jansen, J.D.

2015

We consider robust ensemble-based (EnOpt) multi-objective production optimization of on-off inflow control devices (ICDs) for a sector model inspired on a real-field case. The use of on-off valves as optimization variables leads to a discrete control problem. We propose a re-parameterization of such discrete controls in terms of switching times, i.e. we optimize the time at which a particular valve is either open or closed. This transforms the discrete control problem into a continuous control problem which can be efficiently handled with the EnOpt method. Additionally this leads to a significant reduction in the number of controls which is expected to be beneficial for gradient quality when using approximate gradients. We consider an ensemble of sector models where the uncertainty is described by different permeability, porosity, net-to-gross and initial water saturation fields. The controls are the ICD settings over time in the three horizontal injection wells, with approximately 15 ICDs per well. Different optimized strategies resulting from different initial strategies were compared. We achieved a mean 4.2% increase in expected NPV at a 10% discount rate compared to a traditional pressure maintenance strategy. Next, we performed a sequential bi-objective optimization, and achieved an increase of 9.2% in the secondary objective (25% discounted NPV to emphasize short-term production gains) for a minimal decrease of 1% in the primary objective (0% discounted NPV to emphasize long-term recovery gains), as averaged over the 100 geological realizations. The workflow was repeated for alternative numbers of ICDs showing that having fewer control options lowers the expected value for this particular case. The results demonstrate that ensemble-based optimization workflows are able to produce improved robust recovery strategies for realistic field sector models against acceptable computational cost. Copyright © 2015 Society of Petroleum Engineers.

Geo
PG - Petroleum Geosciences
ELSS - Earth, Life and Social Sciences
Geological Survey Netherlands
Geosciences
2015 Energy
Geology
Horizontal wells
Multiobjective optimization
Petroleum reservoir engineering
Petroleum reservoir evaluation
Secondary recovery
Bi-objective optimization
Ensemble based optimizations
Geological uncertainty

http://resolver.tudelft.nl/uuid:666b63bb-5c88-40f9-8b80-b5a102bb5a43

527765

Society of Petroleum Engineers

9781510800618

Society of Petroleum Engineers - SPE Reservoir Simulation Symposium 2015, 2, 1343-1360

conference paper