Seismic Modelling and Pattern Recognition in Oil Exploration

A. Sinvhal

ISBN 10: 0792314875 / ISBN 13: 9780792314875

Published by Springer Netherlands, Springer Netherlands, 1992

About this Item

Druck auf Anfrage Neuware - Printed after ordering - The reasons for writing this book are very simple. We use and teach com puter aided techniques of mathematical simulation and of pattern recogni tion. Life would be much simpler if we had a suitable text book with methods and computer programmes which we could keep referring to. Therefore, we have presented here material that is essential for mathematical modelling of some complex geological situations, with which earth scientists are often confronted. The reader is introduced not only to the essentials of computer modelling, data analysis and pattern recognition, but is also made familiar with the basic understanding with which they can plunge into when solving related and more complex problems. This book first makes a case for seismic stratigraphy and then for pattern recognition. Chapter 1 provides an extensive review of applications of pattern recognition methods in oil exploration. Simulation procedures are presented with examples that are fairly simple to understand and easy to use on the computer. Several geological situations can be formulated and simulated using the Monte Carlo method. The binary lithologic sequences, discussed in Chapter 2, consist of alternating layers of any two of sand, shale and coal.

Seller Inventory # 9780792314875

Bibliographic Details

• Title: Seismic Modelling and Pattern Recognition in Oil Exploration
• Publisher: Springer Netherlands, Springer Netherlands
• Publication Date: 1992
• Language: English
• ISBN 10: 0792314875
• ISBN 13: 9780792314875
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 15D millimeters 241 millimeters width by 160 millimeters height by 15 millimeters depth
• Weight: 456 grams

About this title

Synopsis

The reasons for writing this book are very simple. We use and teach com­ puter aided techniques of mathematical simulation and of pattern recogni­ tion. Life would be much simpler if we had a suitable text book with methods and computer programmes which we could keep referring to. Therefore, we have presented here material that is essential for mathematical modelling of some complex geological situations, with which earth scientists are often confronted. The reader is introduced not only to the essentials of computer modelling, data analysis and pattern recognition, but is also made familiar with the basic understanding with which they can plunge into when solving related and more complex problems. This book first makes a case for seismic stratigraphy and then for pattern recognition. Chapter 1 provides an extensive review of applications of pattern recognition methods in oil exploration. Simulation procedures are presented with examples that are fairly simple to understand and easy to use on the computer. Several geological situations can be formulated and simulated using the Monte Carlo method. The binary lithologic sequences, discussed in Chapter 2, consist of alternating layers of any two of sand, shale and coal.

Synopsis

Aimed primarily at earth scientists, research workers and engineers who are investigating new techniques and ideas for processing and interpreting large amounts of numerical data, this work meets the long-felt need for a comprehensive text covering various aspects of pattern recognition in a single volume. The treatment starts with a description of seismic modelling, ie the formulation of mathematical models for subsurface geology based on Monte Carlo and Markov chains. It then guides the reader through various steps in pattern recognition, viz identification and automatic extraction of attributes in the time and frequency domains from the seismic response of models. The use of these attributes in pattern recognition is validated by interpreting seismic reflection data as a practical application area. Appropriate computer programs have also been included in the text. An important aspect of this book is that it links subsurface geology with pattern recognition. This work should be of interest to those working in the areas of seismic prospecting, seismic zonation and strong motion modelling as well as to those who deal with data interpretation in other disciplines.