Geomodeling

Overview

Geomodeling applies mathematical methods to the unified modeling of the topology, geometry, and physical properties of geological objects. The methodology (gOcad, computer assisted design of geological data) is general, but in this book the author presents a new interpolation method for modeling natural objects that allows application of a wide range of complex data. The audience for the book will be graduate students and practitioners in the earth and environmental sciences.

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Overview

Geomodeling applies mathematical methods to the unified modeling of the topology, geometry, and physical properties of geological objects. The methodology (gOcad, computer assisted design of geological data) is general, but in this book the author presents a new interpolation method for modeling natural objects that allows application of a wide range of complex data. The audience for the book will be graduate students and practitioners in the earth and environmental sciences.

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Editorial Reviews

From The Critics
Mallet (Institut National Polytechnique de Lorraine, and participant in the gOcad research project) explains the Discrete Smooth Interpolation (DSI) approach to modelling complex surfaces, which has been developed over the last couple of decades to model geological surfaces and geological volumes affected by tectonic events with overturned folds, salt domes, and reverse faults (the modelling software developed for the car industry couldn't do the job). The DSI approach is now also finding applications in fields such as medicine, anthropology, and the environmental sciences. Coverage includes cellular partitions, tesselations, elements of differential geometry, triangulated surfaces, elements of structural geology, stochastic modeling, and discrete smooth partition. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

  • ISBN-13: 9780195144604
  • Publisher: Oxford University Press, USA
  • Publication date: 1/28/2002
  • Series: Applied Geostatistics Series
  • Pages: 624
  • Product dimensions: 9.20 (w) x 6.30 (h) x 1.40 (d)

Meet the Author

Ecole Nationale Superieure de Geologie
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Table of Contents

1 Discrete Modeling for Natural Objects 1
1.1 Introduction 1
1.2 Discrete modeling 5
1.3 Interpolation 12
1.4 Examples of applications 19
1.5 Conclusions 26
2 Cellular Partitions 27
2.1 Introduction 27
2.2 Elements of topology 28
2.3 Cellular partition of an n-manifold object 36
2.4 Generalized Maps 57
2.5 Implementing GMap-based models 81
2.6 Conclusions 93
3 Tessellations 97
3.1 Introduction 97
3.2 Delaunay's tessellation 98
3.3 Non-Delaunay triangulated surfaces 109
3.4 Notion of a regular n-grid 122
3.5 Notion of an irregular n-grid 132
3.6 Implicit surfaces 134
3.7 Conclusions 137
4 Discrete Smooth Interpolation 139
4.1 Introduction 139
4.2 The DSI problem 147
4.3 Uniqueness of the DSI solution 153
4.4 The local DSI equation 160
4.5 Accounting for hard constraints 170
4.6 Accelerating the convergence 174
4.7 The fuzzy Control-Point paradigm 182
4.8 The fuzzy Control-Node paradigm 190
4.9 From a discrete to a continuous model 193
4.10 Conclusions 196
5 Elements of Differential Geometry 199
5.1 Parametric curves 199
5.2 Parametric surfaces 203
5.3 Curvature of curves drawn on a surface 211
5.4 Miscellaneous 218
5.5 Discrete modeling 226
5.6 Examples of applications to geology 233
5.7 Conclusions 244
6 Piecewise Linear Triangulated Surfaces 245
6.1 Introduction 245
6.2 Basic DSI constraints 256
6.3 Modeling a faulted surface 272
6.4 Continuity through faults 278
6.5 Global parameterization 287
6.6 Modifying the topology 305
6.7 Conclusions 315
7 Curvilinear Triangulated Surfaces 317
7.1 Introduction 317
7.2 Building a smooth curvilinear triangle 318
7.3 Gregory G[superscript 1] patchwork 336
7.4 Recursive subdivisions 350
7.5 Conclusions 369
8 Elements of Structural Geology 371
8.1 Geometry of faults and horizons 371
8.2 Modeling stratified media 379
8.3 Merging seismic data with well data 390
8.4 Deformation analysis 392
8.5 Unfolding a horizon 405
8.6 Unfolding a stack of layers 418
8.7 Conclusions 441
9 Stochastic Modeling 443
9.1 Simulation versus interpolation 443
9.2 Probabilities in a nutshell 445
9.3 Random Functions 459
9.4 Random Fourier Series 474
9.5 Uniform Random Functions and P-fields 488
9.6 Stochastic simulators 492
9.7 Kriging-based methods 502
9.8 Blending-based method 519
9.9 Assessing geometric uncertainties 528
9.10 Conclusions 532
10 Discrete Smooth Partition 533
10.1 Introduction 533
10.2 The probabilistic approach 538
10.3 Structural constraints 548
10.4 Moving-Centers-based methods 559
10.5 A tutorial example 572
10.6 Conclusions 579
Index 595
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