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Global optimization methods in geophysical inversion

One of the major goals of geophysical inversion is to find earth models that explain the geophysical observations. Thus the branch of mathematics known as optimization has found significant use in many geophysical applications. Both local and global optimization methods are used in the estimation of material properties from geophysical data. As the title of the book suggests, the aim of this book is to describe the application of several recently developed global optimization methods to geophysical problems. & bull; The well known linear and gradient based optimization methods have been summari.

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  • "One of the major goals of geophysical inversion is to find earth models that explain the geophysical observations. Thus the branch of mathematics known as optimization has found significant use in many geophysical applications. Both local and global optimization methods are used in the estimation of material properties from geophysical data. As the title of the book suggests, the aim of this book is to describe the application of several recently developed global optimization methods to geophysical problems. & bull; The well known linear and gradient based optimization methods have been summari."@en
  • "One of the major goals of geophysical inversion is to find earth models that explain the geophysical observations. Thus the branch of mathematics known as optimization has found significant use in many geophysical applications. Both local and global optimization methods are used in the estimation of material properties from geophysical data. As the title of the book suggests, the aim of this book is to describe the application of several recently developed global optimization methods to geophysical problems. & bull; The well known linear and gradient based optimization methods have been summarized in order to explain their advantages and limitations & bull; The theory of simulated annealing and genetic algorithms have been described in sufficient detail for the readers to understand the underlying fundamental principles upon which these algorithms are based & bull; The algorithms have been described using simple flow charts (the algorithms are general and can be applied to a wide variety of problems Students, researchers and practitioners will be able to design practical algorithms to solve their specific geophysical inversion problems. The book is virtually self-contained so that there are no prerequisites, except for a fundamental mathematical background that includes a basic understanding of linear algebra and calculus."@en
  • "One of the major goals of geophysical inversion is to find earth models that explain the geophysical observations. Thus the branch of mathematics known as optimization has found significant use in many geophysical applications. Both local and global optimization methods are used in the estimation of material properties from geophysical data. As the title of the book suggests, the aim of this book is to describe the application of several recently developed global optimization methods to geophysical problems. & bull; The well known linear and gradient based optimization methods have been summarized in order to explain their advantages and limitations & bull; The theory of simulated annealing and genetic algorithms have been described in sufficient detail for the readers to understand the underlying fundamental principles upon which these algorithms are based & bull; The algorithms have been described using simple flow charts (the algorithms are general and can be applied to a wide variety of problems Students, researchers and practitioners will be able to design practical algorithms to solve their specific geophysical inversion problems. The book is virtually self-contained so that there are no prerequisites, except for a fundamental mathematical background that includes a basic understanding of linear algebra and calculus."
  • ""Making inferences about systems in the Earth's subsurface from remotely-sensed, sparse measurements is a challenging task. Geophysical inversion aims to find models which explain geophysical observations - a model-based inversion method attempts to infer model parameters by iteratively fitting observations with theoretical predictions from trial models. Global optimization often enables the solution of non-linear models, employing a global search approach to find the absolute minimum of an objective function, so that predicted data best fits the observations. This new edition provides an up-to-date overview of the most popular global optimization methods, including a detailed description of the theoretical development underlying each method, and a thorough explanation of the design, implementation, and limitations of algorithms. A new chapter provides details of recently-developed methods, such as the neighborhood algorithm, and particle swarm optimization. An expanded chapter on uncertainty estimation includes a succinct description on how to use optimization methods for model space exploration to characterize uncertainty, and now discusses other new methods such as hybrid Monte Carlo and multi-chain MCMC methods. Other chapters include new examples of applications, from uncertainty in climate modeling to whole earth studies. Several different examples of geophysical inversion, including joint inversion of disparate geophysical datasets, are provided to help readers design algorithms for their own applications. This is an authoritative and valuable text for researchers and graduate students in geophysics, inverse theory, and exploration geoscience, and an important resource for professionals working in engineering and petroleum exploration."--"
  • ""Making inferences about systems in the Earth's subsurface from remotely-sensed, sparse measurements is a challenging task. Geophysical inversion aims to find models which explain geophysical observations - a model-based inversion method attempts to infer model parameters by iteratively fitting observations with theoretical predictions from trial models. Global optimization often enables the solution of non-linear models, employing a global search approach to find the absolute minimum of an objective function, so that predicted data best fits the observations. This new edition provides an up-to-date overview of the most popular global optimization methods, including a detailed description of the theoretical development underlying each method, and a thorough explanation of the design, implementation, and limitations of algorithms. A new chapter provides details of recently-developed methods, such as the neighborhood algorithm, and particle swarm optimization. An expanded chapter on uncertainty estimation includes a succinct description on how to use optimization methods for model space exploration to characterize uncertainty, and now discusses other new methods such as hybrid Monte Carlo and multi-chain MCMC methods. Other chapters include new examples of applications, from uncertainty in climate modeling to whole earth studies. Several different examples of geophysical inversion, including joint inversion of disparate geophysical datasets, are provided to help readers design algorithms for their own applications. This is an authoritative and valuable text for researchers and graduate students in geophysics, inverse theory, and exploration geoscience, and an important resource for professionals working in engineering and petroleum exploration."--"@en
  • "One of the major goals of geophysical inversion is to find earth models that explain the geophysical observations. Thus the branch of mathematics known as optimization has found significant use in many geophysical applications.PBoth local and global optimization methods are used in the estimation of material properties from geophysical data. As the title of the book suggests, the aim of this book is to describe the application of several recently developed global optimization methods to geophysical problems. P• The well known linear and gradient based optimization methods have been summarized in order to explain their advantages and limitationsP• The theory of simulated annealing and genetic algorithms have been described in sufficient detail for the readers to understand the underlying fundamental principles upon which these algorithms are basedP• The algorithms have been described using simple flow charts (the algorithms are general and can be applied to a wide variety of problemsPStudents, researchers and practitioners will be able to design practical algorithms to solve their specific geophysical inversion problems. The book is virtually self-contained so that there are no prerequisites, except for a fundamental mathematical background that includes a basic understanding of linear algebra and calculus."

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  • "Electronic books"@en
  • "Electronic books"
  • "e-book [online only]"@en
  • "Llibres electrònics"

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  • "Global Optimization Methods in Geophysical Inversion. Advances in Exploration Geophysics, Volume 4"
  • "Global optimization methods in geophysical inversion"@en
  • "Global optimization methods in geophysical inversion"
  • "Global Optimization Methods in Geophysical Inversion"
  • "Global Optimization Methods in Geophysical Inversion"@en

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