INSIM-BHP: a physics-based data-driven reservoir model for history matching and forecasting with bottomhole pressure and production rate data under waterflooding

DOI10.1016/j.jcp.2022.111714OpenAlexW4307392575MaRDI QIDQ2106912

Yanyan Li

Publication date: 29 November 2022

Published in: Journal of Computational Physics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jcp.2022.111714

zbMATH Keywords

history matchingpressure calculationdata-driven modelensemble-based data assimilationwaterflood characterization and monitoring

Mathematics Subject Classification ID

Geophysics (86Axx) Geophysics (86-XX) Flows in porous media; filtration; seepage (76Sxx)

Cites Work

• Investigation of the sampling performance of ensemble-based methods with a simple reservoir model
• Ensemble clustering for efficient robust optimization of naturally fractured reservoirs
• Waterflooding optimization with the INSIM-FT data-driven model
• INSIM-FT in three-dimensions with gravity
• An $O(n^2 \log n)$ Time Algorithm for the Minmax Angle Triangulation

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