Theoretical connections between optimization algorithms based on an approximate gradient
From MaRDI portal
Publication:1663476
DOI10.1007/s10596-013-9368-9zbMath1393.90137OpenAlexW2036409858MaRDI QIDQ1663476
Publication date: 21 August 2018
Published in: Computational Geosciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10596-013-9368-9
Numerical mathematical programming methods (65K05) Methods of quasi-Newton type (90C53) Methods of reduced gradient type (90C52) Potentials, prospecting (86A20)
Related Items (15)
Ensemble Gradient for Learning Turbulence Models from Indirect Observations ⋮ Refined ensemble-based waterflooding optimization subject to field-wide constraints ⋮ A machine-learning-accelerated distributed LBFGS method for field development optimization: algorithm, validation, and applications ⋮ A quasi-Newton trust-region method for optimization under uncertainty using stochastic simplex approximate gradients ⋮ A natural Hessian approximation for ensemble based optimization ⋮ Improved sampling strategies for ensemble-based optimization ⋮ Ensemble clustering for efficient robust optimization of naturally fractured reservoirs ⋮ Waterflooding optimization with the INSIM-FT data-driven model ⋮ Gradient-free strategies to robust well control optimization ⋮ Distributed Gauss-Newton optimization method for history matching problems with multiple best matches ⋮ Robust production optimization with capacitance-resistance model as precursor ⋮ Reservoir uncertainty tolerant, proactive control of intelligent wells ⋮ A theoretical look at ensemble-based optimization in reservoir management ⋮ Distributed quasi-Newton derivative-free optimization method for optimization problems with multiple local optima ⋮ A Stochastic Simplex Approximate Gradient (StoSAG) for optimization under uncertainty
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Closed-loop reservoir management on the Brugge test case
- Uncertainty quantification of reservoir performance predictions using a stochastic optimization algorithm
- On optimization algorithms for the reservoir oil well placement problem
- Recent progress on reservoir history matching: a review
- Waterflooding using closed-loop control
- Calculating derivatives for automatic history matching
- Adaptive stochastic approximation by the simultaneous perturbation method
- Using Sampling and Simplex Derivatives in Pattern Search Methods
- Multivariate stochastic approximation using a simultaneous perturbation gradient approximation
- Introduction to Stochastic Search and Optimization
- Detection and Remediation of Stagnation in the Nelder--Mead Algorithm Using a Sufficient Decrease Condition
- Fortified-Descent Simplicial Search Method: A General Approach
This page was built for publication: Theoretical connections between optimization algorithms based on an approximate gradient