Approximate derivative computations for the gradient-based optimization methods in the local gradual deformation for history matching
DOI10.1007/s11004-011-9337-6zbMath1223.65040OpenAlexW2031898075MaRDI QIDQ638572
Publication date: 13 September 2011
Published in: Mathematical Geosciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11004-011-9337-6
inverse problemperturbationnumerical examplesderivativereservoir characterizationobjective functionhistory matchinggradient-based optimizationgeostatistical realizationslocal gradual deformationseismic data
Numerical mathematical programming methods (65K05) Applications of mathematical programming (90C90) Nonlinear programming (90C30) Inverse problems in geophysics (86A22) Computational methods for problems pertaining to geophysics (86-08) Potentials, prospecting (86A20)
Uses Software
Cites Work
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- The probability perturbation method: a new look at Bayesian inverse modeling
- Practical mathematical optimization. An introduction to basic optimization theory and classical and new gradient-based algorithms.
- Gradual deformation and iterative calibration of sequential stochastic simulations
- New methods to color the vertices of a graph
- Sensitivity Analysis in Practice
- Efficient reservoir history matching using subspace vectors
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