Distributed Gauss-Newton optimization method for history matching problems with multiple best matches
From MaRDI portal
Publication:1785159
DOI10.1007/s10596-017-9657-9zbMath1405.90126OpenAlexW2611461852MaRDI QIDQ1785159
Jeroen C. Vink, Mohammadali Tarrahi, Yaakoub El Khamra, Guohua Gao, Chaohui Chen
Publication date: 28 September 2018
Published in: Computational Geosciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10596-017-9657-9
Nonlinear programming (90C30) Derivative-free methods and methods using generalized derivatives (90C56) Methods of successive quadratic programming type (90C55)
Related Items (6)
Gaussian mixture model fitting method for uncertainty quantification by conditioning to production data ⋮ Performance enhancement of Gauss-Newton trust-region solver for distributed Gauss-Newton optimization method ⋮ A machine-learning-accelerated distributed LBFGS method for field development optimization: algorithm, validation, and applications ⋮ Constrained iterative ensemble smoother for multi solution search assisted history matching ⋮ Using a machine learning proxy for localization in ensemble data assimilation ⋮ Distributed quasi-Newton derivative-free optimization method for optimization problems with multiple local optima
Uses Software
Cites Work
- Unnamed Item
- Optimization by Simulated Annealing
- Filtering with state space localized Kalman gain
- Large-scale history matching with quadratic interpolation models
- Uncertainty quantification of reservoir performance predictions using a stochastic optimization algorithm
- Gradient-based multi-objective optimization with applications to waterflooding optimization
- On solving trust-region and other regularised subproblems in optimization
- Theoretical connections between optimization algorithms based on an approximate gradient
- Levenberg-Marquardt forms of the iterative ensemble smoother for efficient history matching and uncertainty quantification
- Least Frobenius norm updating of quadratic models that satisfy interpolation conditions
- Recent progress on reservoir history matching: a review
- Uncertainty quantification for porous media flows
- Adaptive stochastic approximation by the simultaneous perturbation method
- A Trust-Region Approach to the Regularization of Large-Scale Discrete Forms of Ill-Posed Problems
- Inverse problems: A Bayesian perspective
- Minimization of a Large-Scale Quadratic FunctionSubject to a Spherical Constraint
- Computing a Trust Region Step
- Developments of NEWUOA for minimization without derivatives
- Algorithm 856
- Iterative Methods for Finding a Trust-region Step
- `` Direct Search Solution of Numerical and Statistical Problems
- Numerical Optimization
- Information-Driven Distributed Maximum Likelihood Estimation Based on Gauss-Newton Method in Wireless Sensor Networks
- Inverse Problem Theory and Methods for Model Parameter Estimation
- Benchmarking Derivative-Free Optimization Algorithms
- Metropolized Randomized Maximum Likelihood for Improved Sampling from Multimodal Distributions
- A Stochastic Simplex Approximate Gradient (StoSAG) for optimization under uncertainty
- Marginalized particle filters for mixed linear/nonlinear state-space models
- Mesh Adaptive Direct Search Algorithms for Constrained Optimization
- A Simplex Method for Function Minimization
- Data Assimilation
- Global convergence of a regularized factorized quasi-Newton method for nonlinear least squares problems
This page was built for publication: Distributed Gauss-Newton optimization method for history matching problems with multiple best matches
