Seismic data interpretation using digital image processing

Description

Content: Cover Title Page Copyright Contents Foreword Preface Chapter 1 Introduction 1.1 Image Processing of Exploration Seismic Data 1.2 Exploration Seismic Data: From Acquisition to Interpretation 1.2.1 Seismic Data Acquisition 1.2.2 Seismic Data Processing 1.2.3 Seismic Data Interpretation 1.3 The Seismic Convolution Model 1.4 Summary Chapter 2 Seismic Data Interpretation 2.1 Introduction 2.2 Structural Features 2.2.1 Faults 2.2.2 Folds 2.2.3 Diapirs 2.3 Stratigraphic Features 2.3.1 Channels 2.3.2 Reefs 2.3.3 Truncation 2.4 Seismic Interpretation Tools 2.4.1 Seismic Sequence Stratigraphy2.4.2 Seismic Facies Analysis 2.4.3 Direct Hydrocarbon Indicators 2.4.4 Tying Seismic and Well Data 2.4.5 Seismic Modeling 2.4.6 Time-to-Depth Conversion 2.4.7 Seismic Attributes 2.5 Pitfalls in Seismic Interpretation 2.6 Summary 2.7 Problems and Computer Assignments Chapter 3 Seismic Image Enhancement in the Spatial Domain 3.1 Introduction 3.1.1 The Mean (Running-Average) Filter 3.2 The Median Filter 3.3 The Edge-Preserving Smoothing Algorithm 3.3.1 Two-Dimensional Structure-Preserving Smoothing 3.4 Wavelet-Based Smoothing 3.4.1 Method 3.4.2 Sharpening Filter3.5 Summary 3.6 Problems and Computer Assignments Chapter 4 Seismic Image Enhancement in the Spectral Domain 4.1 Introduction 4.2 The Fourier Transform 4.3 Filtering in the Spectral Domain 4.4 Spectral Attributes 4.5 Summary 4.6 Problems and Computer Assignments Chapter 5 Seismic Attributes 5.1 Introduction 5.2 Detection of Interesting Regions from Time or Depth Three-Dimensional Slices using Seismic Attributes 5.3 Two-Dimensional Numerical Gradient Edge-Detector Operators 5.4 Application to Real Seismic Data 5.5 Two-Dimensional Second-Order Derivative Operator5.5.1 The Coherence Attribute 5.5.2 The Dip Attribute 5.6 The Curvature Attribute 5.7 Curvature of the Surface 5.7.1 Curve, Velocity, and Curvature 5.7.2 Surface, Tangent Plane, and Norm 5.8 Shape Operator, Normal Curvature, and Principal Curvature 5.8.1 Normal Curvature 5.8.2 Shape Operator 5.8.3 The Principal Curvatures 5.8.4 Calculation of the Principal Curvatures 5.8.5 Summary of Calculation of Principal Curvature for a Surface 5.9 The Randomness Attribute 5.10 Technique for Two-Dimensional Images 5.10.1 Problem Statement and Preliminaries5.10.2 Review of Fast Noise Variance Estimation Algorithm 5.10.3 Design Mask by Constrained Optimization 5.11 The Spectral Decomposition Attribute 5.12 Summary 5.13 Problems and Computer Assignments Chapter 6 Color Display of Seismic Images 6.1 Introduction 6.2 Color Models and Useful Color Bars 6.2.1 The RGB Model 6.2.2 The CMY Model 6.2.3 The HSI Model 6.2.4 Useful Color Bars 6.3 Overlay and Mixed Displays of Seismic Attribute Images 6.4 Summary 6.5 Problems and Computer Assignments Chapter 7 Seismic Image Segmentation