Geophysical Data Analysis Understanding Inverse Problem Theory And Practice
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Geophysical Data Analysis: Understanding Inverse Problem Theory and Practice
Geophysical data analysis is a very practical subject and this book is intended to be a simple guide to the techniques of parameter estimation and error analysis. I have placed emphasis on the reconciliation of theory and practical data to enable the reader understand how to tackle typical problems in data analysis. It is hoped that a mastery of the simple techniques described in this book will inspire confidence in the reader to consult the more classical treatment of the subject. It is pertinent to mention that this book developed out of a highly successful course of the same title given to senior undergraduate geophysics students in Leicester University since 1988 and its popularity stems from the structured learning programs and the simple effective practical approach to geophysical inversion. The course is given in the first semester to provide students with the basic tools for quantitative analysis of geoscientific data and consists of 10 lectures and practical sessions involving the materials given in Chapters 1 to 9 in this book. Chapter 10 derives from topical issues of research interest to me and my induction courses for postgraduate students in geophysics and the industry. The contents of this book are easily digestible and require little statistical or mathematical commitment.
Geophysical Data Analysis: Discrete Inverse Theory
"The treatment of inverse theory in this book is divided into four parts. Chapters 1 and 2 provide a general background, explaining what inverse problems are and what constitutes their solution as well as reviewing some of the basic concepts from linear algebra and probability theory that will be applied throughout the text. Chapters 3-7 discuss the solution of the canonical inverse problem: the linear problem with Gaussian statistics. This is the best understood of all inverse problems; and it is here that the fundamental notions of uncertainty, uniqueness, and resolution can be most clearly developed. Chapters 8-11 extend the discussion to problems that are non-Gaussian, nonlinear and continuous. Chapters 12-13 provide examples of the use of inverse theory and a discussion of the steps that must be taken to solve inverse problems on a computer"--
Geophysical Data Analysis
Geophysical Data Analysis: Diverse Inverse Theory, Fourth Edition is a revised and expanded introduction to inverse theory and tomography as it is practiced by geophysicists. It demonstrates the methods needed to analyze a broad spectrum of geophysical datasets, with special attention to those methods that generate images of the earth. Data analysis can be a mathematically complex activity, but the treatment in this volume is carefully designed to emphasize those mathematical techniques that readers will find the most familiar and to systematically introduce less-familiar ones. Using problems and case studies, along with MATLAB computer code and summaries of methods, the book provides data scientists and engineers in geophysics with the tools necessary to understand and apply mathematical techniques and inverse theory. - Includes material on probability, including Bayesian influence, probability density function and metropolis algorithm - Offers detailed discussion of the application of inverse theory to tectonic, gravitational and geomagnetic studies - Contains numerous examples, color figures and end-of-chapter homework problems to help readers explore and further understand presented ideas - Includes MATLAB examples and problem sets - Updated and refined throughout to bring the text in line with current understanding and improved examples and case studies - Expanded sections to cover material, such as second-derivation smoothing and chi-squared tests not covered in the previous edition