Compressed history matching: Exploiting transform-domain sparsity for regularization of nonlinear dynamic data integration problems

DOI10.1007/s11004-009-9247-zzbMath1185.94011OpenAlexW2010762552MaRDI QIDQ848925

Dennis B. McLaughlin, William T. Freeman, Behnam Jafarpour, Vivek K. Goyal

Publication date: 23 February 2010

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

Full work available at URL: https://doi.org/10.1007/s11004-009-9247-z

zbMATH Keywords

regularizationparameterizationsparsityhistory matchingcompressed sensingfacies characterization

Mathematics Subject Classification ID

Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Computer-aided design (modeling of curves and surfaces) (65D17) Geophysics (86A99)

Related Items (12)

Prior model identification during subsurface flow data integration with adaptive sparse representation techniques ⋮ A new differentiable parameterization based on principal component analysis for the low-dimensional representation of complex geological models ⋮ Geological facies recovery based on weighted \(\ell_1\)-regularization ⋮ Recent progress on reservoir history matching: a review ⋮ Large-scale history matching with quadratic interpolation models ⋮ Parametric generation of conditional geological realizations using generative neural networks ⋮ Efficient uncertainty quantification for dynamic subsurface flow with surrogate by theory-guided neural network ⋮ Data assimilation and uncertainty assessment for complex geological models using a new PCA-based parameterization ⋮ Regularized kernel PCA for the efficient parameterization of complex geological models ⋮ Efficient uncertainty quantification of reservoir properties for parameter estimation and production forecasting ⋮ A pattern-matching method for flow model calibration under training image constraint ⋮ A deep-learning-based geological parameterization for history matching complex models

Uses Software

• L-BFGS
• PDCO
• ECLIPSE

Cites Work

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