Prior model identification during subsurface flow data integration with adaptive sparse representation techniques
From MaRDI portal
Publication:1663631
DOI10.1007/s10596-013-9378-7zbMath1393.76120OpenAlexW2068868543MaRDI QIDQ1663631
Behnam Jafarpour, Mohammadreza M. Khaninezhad
Publication date: 22 August 2018
Published in: Computational Geosciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10596-013-9378-7
Related Items
Reducing uncertainty in conceptual prior models of complex geologic systems via integration of flow response data, Convolutional neural networks (CNN) for feature-based model calibration under uncertain geologic scenarios
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Enhancing sparsity by reweighted \(\ell _{1}\) minimization
- Compressed history matching: Exploiting transform-domain sparsity for regularization of nonlinear dynamic data integration problems
- Boosting iterative stochastic ensemble method for nonlinear calibration of subsurface flow models
- Uncertainty Principles and Signal Recovery
- Effective solution of nonlinear subsurface flow inverse problems in sparse bases
- Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
- Sparse and Redundant Representations
- From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images
- Atomic Decomposition by Basis Pursuit
- $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
- Sparse Approximate Solutions to Linear Systems
- Matching pursuits with time-frequency dictionaries
- Compressed sensing
