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  • 200pp. Published April 2018
  • Scientific Research Publishing, Inc., USA
  • Category: Earth & Environmental Sciences
  • ISBN: 978-1-61896-525-7
  • (Paperback) USD 89.00
  • ISBN: 978-1-61896-526-4
  • (E-Book) USD 29.00

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Home > Books > Geophysical Inversion Theory and Global ...
Geophysical Inversion Theory and Global Optimization Methods
  • Description
  • E-Book
  • Author(s) Information

Geophysical inversion is an ill-posed problem. Classical local search method for inversion is depend on initial guess and easy to be trapped in local optimum. The global optimization is a group of novel methods to deal with the problems mentioned above.

The book introduces the geophysical inversion theory, including the classical solving approaches firstly. Then, it introduces several typical global inversion approaches including particle swarm optimization (PSO), differential evolution (DE), and multiobjective optimization methods, as well as some examples to inverse the geophysical data, such as gravity, MT sounding, well logging, self-potential, seismic data, using these global optimization approaches.
Components of the Book:
  • Front Matter
  • Chapter 1 Forward and inverse problem in geophysics
    • 1.1. Introduction
    • 1.2. Formulation of forward and inverse problem
    • 1.3. Existence and uniqueness of inversion problem solutions
    • References
  • Chapter 2 Foundation of Ill-posed problems and regularization methods
    • 2.1. Introduction
    • 2.2. Sensitivity and resolution of geophysical methods
    • 2.3. Formulation of well-posed and ill-posed problems
    • 2.4. Foundations of regularization methods of inverse problem solution
    • References
  • Chapter 3 Direct linear inverse methods
    • 3.1. Linear least-squares inversion
    • 3.2. Solution of the purely underdetermined problem
    • 3.3 Weighted least-squares method
    • 3.4 Regularization methods
    • References
  • Chapter 4 Iterative linear inverse methods
    • 4.1. Iterative method for linear equations
    • 4.2. A generalized minimal residual method
    • 4.3. The regularization method in linear inversion
    • References
  • Chapter 5 Nonlinear inverse methods
    • 5.1. Gradient-type methods
    • 5.2. Regularized gradient method
    • 5.3. Regularized nonlinear inversion method
    • References
  • Chapter 6 Particle Swarm Optimization methods
    • 6.1. Introduction
    • 6.2. PSO for MT data inversion
    • 6.3. PSO for Well logging data inversion
    • 6.4. PSO inversion for gravity data
    • 6.5. PSO inversion for self-potential data
    • 6.6. Parallel PSO inversion
    • 6.7. Uncertainty Assessment
    • References
  • Chapter 7 Differential Evolution methods
    • 7.1. Introduction
    • 7.2. DE for MT data inversion
    • 7.3. DE for Well logging data inversion
    • 7.4. DE for prestack seismic data inversion
    • 7.5. DE for geoelectircal data inversion
    • References
  • Chapter 8 Multiobjective Optimization methods
    • 8.1. Introduction
    • 8.2. Multiobjective regularization inversion
    • 8.3. Multiobjective joint inversion
    • 8.4. Cloud-based geophysical Inversion
    • References
Readership: Scientists and Researchers
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