• формат pdf
  • размер 11.03 МБ
  • добавлен 24 мая 2010 г.
Davis J.C. Statistics and Data Analysis in Geology (3rd ed.)
3rd Ed, John Wiley & Sons, 2002. ISBN: 0471172758.
Thoroughly revised and updated, this new edition of the text that helped define the field continues to present important methods in the quantitative analysis of geologic data, while showing students how statistics and computing can be applied to commonly encountered problems in the earth sciences.
In addition to new and expanded coverage of key topics, the Third Edition features new pedagogy, end-of-chapter review exercises, and an accompanying website that contains all of the data for every example and exercise found in the book.
This thoroughly revised edition presents important methods in the quantitative analysis of geologic data. Retains the basic arrangement of the previous edition but expands sections on probability, nonparametric statistics, and Fourier analysis. Contains revised coverage of eigenvalues and eigenvectors, and new coverage of data analysis methods, such as the semivariogram and the process of kriging.
Читать онлайн
Смотрите также

Dubrule O. Geostatistics for Seismic Data Integration in Earth Models

  • формат pdf
  • размер 57.43 МБ
  • добавлен 06 июня 2011 г.
Tulsa, Society of Exploration Geophysicists & European Association of Geoscientists and Engineers, 2003. –281 pp. Table of Contents Introduction The Covariance and the Variogram Interpolation: Kriging, Cokriging, Factorial Kriging and Splines Conditional simulation for Heterogeneity Modeling and Uncertainty Quantification Geostatistical Inversion Stochastic Earth Modeling That Integrates All Subsurface Uncertainties Conclusions Exercises Not...

Freeden W. et al. (eds.) Handbook of GeoMathematics

  • формат pdf
  • размер 24.47 МБ
  • добавлен 14 ноября 2011 г.
Springer, 2010. – 1338 pp. ISBN 9783642015458. Mathematics concerned with problems of geoscientifical relevance, i.e., geomathematics, is becoming increasingly important. Surprisingly, there is no authoritative mathematical forum offering appropriate means of assimilating, assessing, and reducing to comprehensible form the readily increasing flow of data from geochemical, geodetic, geological, geophysical, and satellite sources and providing an o...

Jean-Laurent Mallet. Geomodeling

  • формат pdf
  • размер 34 МБ
  • добавлен 20 октября 2010 г.
Oxford University Press, 2002. (англ. ). Contents. Discrete Modeling for Natural Objects. Cellular Partitions. Tessellations. Discrete Smooth Interpolation. Elements of Differential Geometry. Piecewise Linear Triangulated Surfaces. Curvilinear Triangulated Surfaces. Elements of Structural Geology. Stochastic Modeling. Discrete Smooth Partition.

Paradigm. Руководство пользователя для программного продукта Gocad 2.7

  • формат pdf
  • размер 78.57 МБ
  • добавлен 25 февраля 2011 г.
Paradigm, 2008, язык англ. Gocad - программный продукт для построения трехмерных цифровых геологических моделей. в руководство входят следующие части: Getting Started Data Import and Export Visualization Foundation Modeling and Editing Seismic Interpretation Velocity Modeling Geologic Interpretation 3D Grid Building Reservoir Modeling Reservoir Production and Simulation

Richards J.A., Jia X. Remote Sensing Digital Image Analysis: An Introduction

  • формат pdf
  • размер 8.33 МБ
  • добавлен 11 марта 2011 г.
The book provides the non-specialist with an introduction to quantitative evaluation of satellite and aircraft derived from remotely retrieved data. Each chapter covers the pros and cons of digital remotely sensed data, without detailed mathematical treatment of computer based algorithms, but in a manner conductive to an understanding of their capabilities and limitations. Problems conclude each chapter 4th Edition 2005, 439р.

Sarma D.D. Geostatistics with Applications in Earth Sciences

  • формат pdf
  • размер 13.72 МБ
  • добавлен 11 октября 2011 г.
Capital Publishing Company and Springer, 2009, pages 205. This book has been designed to serve as a text book for post graduate-students and research workers in earth sciences who require a background of and a feel for statistics and the theory of regionalised variables. The book is titled 'Geostatistics with Applications in Earth Sciences". This new edition has been completely revised to reflect the notable concept - and technique-wise in geost...

Steve M., Darby D.M., Geostatistics Explained - An Introductory Guide for Earth Scientists

  • формат pdf
  • размер 2.92 МБ
  • добавлен 27 июня 2010 г.
Cambridge University Press, 2010, ISBN 0521746566. A reader-friendly introduction to geostatistics for students and researchers struggling with statistics. Using simple, clear explanations for introductory and advanced material, it demystifies complex concepts and makes formulas and statistical tests easy to apply. Beginning with a critical evaluation of experimental and sampling design, the book moves on to explain essential concepts of probabil...

Trauth M.H., MATLAB® Recipes for Earth Sciences, Third edition

  • формат pdf
  • размер 11.7 МБ
  • добавлен 05 июля 2010 г.
Springer, 2010, ISBN 3642127614. MATLAB® is used in a wide range of applications in geosciences, such as image processing in remote sensing, generation and processing of digital elevation models and the analysis of time series. This book introduces methods of data analysis in geosciences using MATLAB such as basic statistics for univariate, bivariate and multivariate datasets, jackknife and bootstrap resampling schemes, processing of digital elev...

Webster R., Oliver M.A., Geostatistics for Environmental Scientists

  • формат pdf
  • размер 5.15 МБ
  • добавлен 21 мая 2010 г.
2nd Edition, John Wiley & Sons, 2007, ISBN 978-0-470-02858-2 Geostatistics is essential for environmental scientists. Weather and climate vary from place to place, soil varies at every scale at which it is examined, and even man-made attributes – such as the distribution of pollution – vary. The techniques used in geostatistics are ideally suited to the needs of environmental scientists, who use them to make the best of sparse data for predic...