Assimilating spatially dense data for subsurface applications -- balancing information and degrees of freedom

DOI10.1007/s10596-018-9755-3zbMath1406.86016OpenAlexW2887676175MaRDI QIDQ1715367

Kristian Fossum, Trond Mannseth

Publication date: 4 February 2019

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

Full work available at URL: https://doi.org/10.1007/s10596-018-9755-3

zbMATH Keywords

coarse-scale simulationensemble-based history matchinginverted seismic datareduced data space

Mathematics Subject Classification ID

Seismology (including tsunami modeling), earthquakes (86A15) Inverse problems in geophysics (86A22) Geostatistics (86A32)

Related Items (5)

Iterative multilevel assimilation of inverted seismic data ⋮ A multiscale method for data assimilation ⋮ Assimilation of multiple linearly dependent data vectors ⋮ Sequential multilevel assimilation of inverted seismic data ⋮ Batch seismic inversion using the iterative ensemble Kalman smoother

Uses Software

• EnKF

Cites Work

• Ensemble-based conditioning of reservoir models to seismic data
• Levenberg-Marquardt forms of the iterative ensemble smoother for efficient history matching and uncertainty quantification
• Coarse-scale data assimilation as a generic alternative to localization
• Upscaling: a review
• Iterative Solution Methods
• The ensemble Kalman filter for combined state and parameter estimation

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