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Multi-criterion based well placement and control in the water-flooding of naturally fractured reservoir

Bagherinezhad, A ; Sharif University of Technology | 2017

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  1. Type of Document: Article
  2. DOI: 10.1016/j.petrol.2016.11.013
  3. Publisher: Elsevier B.V , 2017
  4. Abstract:
  5. In the optimization of naturally fractured reservoirs, it is required to take into account their complex flow behavior due to high conductivity fractures. In this regard, the possible effects of fractures must be included in the optimization procedure. In a water-flooding project, fast water breakthrough from injection to production wells may be occurred because of high permeability fractures. To consider the effect of the fracture system, a multi-criterion optimization procedure is proposed in this work. For this contribution, Non-dominated Sorting Genetic Algorithm version II (NSGA-II) is implemented for the optimization purposes. Considering the effect of the fracture system on the flow behavior and consequently, development scenarios, the water breakthrough time is regarded as the objective in addition to ultimate oil recovery. The procedure is applied for well placement and control problems subject to maximization of the cumulative oil production and minimization of water front velocity (or respectively maximization of water breakthrough time). The problems cover design of well configuration and also time-varying bottom-hole pressures. Geological fracture uncertainty in terms of fracture permeability realizations is taken into account for the last optimization problem. This enables decision-makers to select the best scenario by a trade-off between the objectives which are maximization of expected reservoir performance and reducing the risk associated with the worst-case scenario. For this optimization problem under uncertainty, the significance of water breakthrough time expected value as an objective on the robust optimization problem is investigated. © 2016 Elsevier B.V
  6. Keywords:
  7. Fractured reservoir ; Multi-criterion optimization ; NSGA-II ; Well placement ; Bottom hole pressure ; Decision making ; Economic and social effects ; Floods ; Fracture ; Genetic algorithms ; Oil well flooding ; Optimization ; Petroleum reservoirs ; Reservoirs (water) ; Risk perception ; Water injection ; Well flooding ; Optimization under uncertainty ; Well control ; Injection (oil wells) ; Flooding ; Genetic algorithm ; Hydrocarbon reservoir ; Oil production ; Permeability ; Uncertainty analysis
  8. Source: Journal of Petroleum Science and Engineering ; Volume 149 , 2017 , Pages 675-685 ; 09204105 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/abs/pii/S0920410516309986