Waterflooding optimization with the INSIM-FT data-driven model

DOI10.1007/s10596-018-9723-yzbMath1405.76052OpenAlexW2791142891MaRDI QIDQ1710367

Zhenyu Guo, Hui Zhao, Albert C. Reynolds

Publication date: 22 January 2019

Published in: Computational Geosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10596-018-9723-y

zbMATH Keywords

reservoir managementdata-drivenproduction optimizationwaterflooding

Mathematics Subject Classification ID

Hydrology, hydrography, oceanography (86A05) Flows in porous media; filtration; seepage (76S05)

Related Items (5)

Учет геолого-технических мероприятий при моделировании разработки нефтяной залежи методом материального баланса ⋮ A connection element method: both a new computational method and a physical data-driven framework -- take subsurface two-phase flow as an example ⋮ INSIM-FT in three-dimensions with gravity ⋮ An intelligent multi-fidelity surrogate-assisted multi-objective reservoir production optimization method based on transfer stacking ⋮ INSIM-BHP: a physics-based data-driven reservoir model for history matching and forecasting with bottomhole pressure and production rate data under waterflooding

Cites Work

• A numerical method for first order nonlinear scalar conservation laws in one-dimension
• Theoretical connections between optimization algorithms based on an approximate gradient
• Use of reduced-order models in well control optimization
• Reduced-order optimal control of water flooding using proper orthogonal decomposition

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