Detection of Bright Spots Using Pattern Recognition Techniques
Author: Kou-Yuan Huang
Publisher:
Published: 1982
Total Pages: 28
ISBN-13:
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Detection of Bright Spots in Seismic Signal Using Pattern Recognition Techniques
Author: K. Y. Huang
Publisher:
Published: 1983
Total Pages: 263
ISBN-13:
DOWNLOAD EBOOKBright spot is one of the pattern classes in a seismic section and the indicators of gas (hydrocarbon) accumulation. In the past, detection of bright spots depended primarily upon visual examination and the experience of a geophysicist. It is the author's contention that bright spot detection could be made more confidently by computer-aided analysis. This study concerns with two computer-aided methods. One is the decision-theorectic pattern recognition, the other is the syntactic or structural patterns recognition. Using these two methods, a seismogram is classified into two classes, i.e., bright spot and non-bright spot.
Syntactic Pattern Recognition for Seismic Oil Exploration
Author: Kou-Yuan Huang
Publisher: World Scientific
Published: 2002-01-01
Total Pages: 152
ISBN-13: 9789812775740
DOWNLOAD EBOOKThe use of pattern recognition has become more and more important in seismic oil exploration. Interpreting a large volume of seismic data is a challenging problem. Seismic reflection data in the one-shot seismogram and stacked seismogram may contain some structural information from the response of the subsurface. Syntactic/structural pattern recognition techniques can recognize the structural seismic patterns and improve seismic interpretations. The syntactic analysis methods include: (1) the error-correcting finite-state parsing, (2) the modified error-correcting Earley's parsing, (3) the parsing using the match primitive measure, (4) the Levenshtein distance computation, (5) the likelihood ratio test, (6) the error-correcting tree automata, and (7) a hierarchical system. Syntactic seismic pattern recognition can be one of the milestones of a geophysical intelligent interpretation system. The syntactic methods in this book can be applied to other areas, such as the medical diagnosis system. The book will benefit geophysicists, computer scientists and electrical engineers. Sample Chapter(s). Chapter 1: Introduction to Syntactic Pattern Recognition (114 KB). Contents: Introduction to Syntactic Pattern Recognition; Introduction to Formal Languages and Automata; Error-Correcting Finite-State Automaton for Recognition of Ricker Wavelets; Attributed Grammar and Error-Correcting Earley's Parsing; Attributed Grammar and Match Primitive Measure (MPM) for Recognition of Seismic Wavelets; String Distance and Likelihood Ratio Test for Detection of Candidate Bright Spot; Tree Grammar and Automaton for Seismic Pattern Recognition; A Hierarchical Recognition System of Seismic Patterns and Future Study. Readership: Geophysicists, computer scientists and electrical engineers.
Automated Pattern Analysis in Petroleum Exploration
Author: Ibrahim Palaz
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 315
ISBN-13: 1461243882
DOWNLOAD EBOOKHere is a state-of-the-art survey of artificial intelligence in modern exploration programs. Focussing on standard exploration procedures, the contributions examine the advantages and pitfalls of using these new techniques, and, in the process, provide new, more accurate and consistent methods for solving old problems. They show how expert systems can provide the integration of information that is essential in the petroleum industry when solving the complicated questions facing the modern petroleum geoscientist.
Scientific and Technical Aerospace Reports
Author:
Publisher:
Published: 1992
Total Pages: 1572
ISBN-13:
DOWNLOAD EBOOKHandbook of Pattern Recognition and Computer Vision
Author: C. H. Chen
Publisher: World Scientific
Published: 1993-08
Total Pages: 1000
ISBN-13: 9789810222765
DOWNLOAD EBOOK"The book provides an up-to-date and authoritative treatment of pattern recognition and computer vision, with chapters written by leaders in the field. On the basic methods in pattern recognition and computer vision, topics range from statistical pattern recognition to array grammars to projective geometry to skeletonization, and shape and texture measures."--BOOK JACKET.
Seismic Modelling and Pattern Recognition in Oil Exploration
Author: A. Sinvhal
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 199
ISBN-13: 9401125708
DOWNLOAD EBOOKThe 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.
Syntactic Pattern Recognition
Author: Flasinski Mariusz
Publisher: World Scientific
Published: 2019-03-25
Total Pages: 404
ISBN-13: 981327848X
DOWNLOAD EBOOKThis unique compendium presents the major methods of recognition and learning used in syntactic pattern recognition from the 1960s till 2018. Each method is introduced firstly in a formal way. Then, it is explained with the help of examples and its algorithms are described in a pseudocode. The survey of the applications contains more than 1,000 sources published since the 1960s. The open problems in the field, the challenges and the determinants of the future development of syntactic pattern recognition are discussed.This must-have volume provides a good read and serves as an excellent source of reference materials for researchers, academics, and postgraduate students in the fields of pattern recognition, machine perception, computer vision and artificial intelligence.
Handbook of Pattern Recognition & Computer Vision
Author: Chi-hau Chen
Publisher: World Scientific
Published: 1999
Total Pages: 1045
ISBN-13: 9810230710
DOWNLOAD EBOOKAnnotation. Presents the latest research findings in theory, techniques, algorithms, and major applications of pattern recognition and computer vision, as well as new hardware and architecture aspects. Contains sections on basic methods in pattern recognition and computer vision, nine recognition applications, inspection and robotic applications, and architectures and technology. Some areas discussed include cluster analysis, 3D vision of dynamic objects, speech recognition, computer vision in food handling, and video content analysis and retrieval. This second edition is extensively revised to describe progress in the field since 1993. Chen is affiliated with the electrical and computer engineering department at the University of Massachusetts-Dartmouth. Annotation copyrighted by Book News, Inc., Portland, OR.
Pattern Recognition and Image Analysis
Author: Joan MartÃ
Publisher: Springer
Published: 2007-07-07
Total Pages: 674
ISBN-13: 354072849X
DOWNLOAD EBOOKPart of a two-volume set, this book constitutes the refereed proceedings of the Third Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2007, held in Girona, Spain in June 2007. It covers pattern recognition, human language technology, special architectures and industrial applications, motion analysis, image analysis, biomedical applications, shape and texture analysis, 3D, and image coding and processing.
