Seismic Modelling and Pattern Recognition in Oil Exploration
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

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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.

Seismic Attributes as the Framework for Data Integration Throughout the Oilfield Life Cycle
Seismic Attributes as the Framework for Data Integration Throughout the Oilfield Life Cycle

Author: Kurt J. Marfurt

Publisher: SEG Books

Published: 2018-01-31

Total Pages: 509

ISBN-13: 1560803517

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Useful attributes capture and quantify key components of the seismic amplitude and texture for subsequent integration with well log, microseismic, and production data through either interactive visualization or machine learning. Although both approaches can accelerate and facilitate the interpretation process, they can by no means replace the interpreter. Interpreter “grayware” includes the incorporation and validation of depositional, diagenetic, and tectonic deformation models, the integration of rock physics systematics, and the recognition of unanticipated opportunities and hazards. This book is written to accompany and complement the 2018 SEG Distinguished Instructor Short Course that provides a rapid overview of how 3D seismic attributes provide a framework for data integration over the life of the oil and gas field. Key concepts are illustrated by example, showing modern workflows based on interactive interpretation and display as well as those aided by machine learning.

Seismic Attributes for Prospect Identification and Reservoir Characterization
Seismic Attributes for Prospect Identification and Reservoir Characterization

Author: Satinder Chopra

Publisher: SEG Books

Published: 2007

Total Pages: 474

ISBN-13: 1560801417

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Introducing the physical basis, mathematical implementation, and geologic expression of modern volumetric attributes including coherence, dip/azimuth, curvature, amplitude gradients, seismic textures, and spectral decomposition, the authors demonstrate the importance of effective colour display and sensitivity to seismic acquisition and processing.

Geohazards
Geohazards

Author: Madhavi Latha Gali

Publisher: Springer Nature

Published: 2020-08-13

Total Pages: 753

ISBN-13: 9811562334

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This volume comprises select papers presented during the Indian Geotechnical Conference 2018. This volume discusses concepts of soil dynamics and studies related to earthquake geotechnical engineering, slope stability, and landslides. The papers presented in this volume analyze failures connected to geotechnical and geological origins to improve professional practice, codes of analysis and design. This volume will prove useful to researchers and practitioners alike.

Soft Computing and Intelligent Data Analysis in Oil Exploration
Soft Computing and Intelligent Data Analysis in Oil Exploration

Author: M. Nikravesh

Publisher: Elsevier

Published: 2003-04-22

Total Pages: 755

ISBN-13: 0080541321

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This comprehensive book highlights soft computing and geostatistics applications in hydrocarbon exploration and production, combining practical and theoretical aspects.It spans a wide spectrum of applications in the oil industry, crossing many discipline boundaries such as geophysics, geology, petrophysics and reservoir engineering. It is complemented by several tutorial chapters on fuzzy logic, neural networks and genetic algorithms and geostatistics to introduce these concepts to the uninitiated. The application areas include prediction of reservoir properties (porosity, sand thickness, lithology, fluid), seismic processing, seismic and bio stratigraphy, time lapse seismic and core analysis.There is a good balance between introducing soft computing and geostatistics methodologies that are not routinely used in the petroleum industry and various applications areas. The book can be used by many practitioners such as processing geophysicists, seismic interpreters, geologists, reservoir engineers, petrophysicist, geostatistians, asset mangers and technology application professionals. It will also be of interest to academics to assess the importance of, and contribute to, R&D efforts in relevant areas.

Handbook of Pattern Recognition and Computer Vision
Handbook of Pattern Recognition and Computer Vision

Author: C. H. Chen

Publisher: World Scientific

Published: 1993-08

Total Pages: 1000

ISBN-13: 9789810222765

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"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.

Syntactic Pattern Recognition
Syntactic Pattern Recognition

Author: Mariusz Flasinski

Publisher: World Scientific

Published: 2019-03-25

Total Pages: 403

ISBN-13: 981327848X

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This 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.

Enhance Oil and Gas Exploration with Data-Driven Geophysical and Petrophysical Models
Enhance Oil and Gas Exploration with Data-Driven Geophysical and Petrophysical Models

Author: Keith R. Holdaway

Publisher: John Wiley & Sons

Published: 2017-09-28

Total Pages: 369

ISBN-13: 1119302595

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Leverage Big Data analytics methodologies to add value to geophysical and petrophysical exploration data Enhance Oil & Gas Exploration with Data-Driven Geophysical and Petrophysical Models demonstrates a new approach to geophysics and petrophysics data analysis using the latest methods drawn from Big Data. Written by two geophysicists with a combined 30 years in the industry, this book shows you how to leverage continually maturing computational intelligence to gain deeper insight from specific exploration data. Case studies illustrate the value propositions of this alternative analytical workflow, and in-depth discussion addresses the many Big Data issues in geophysics and petrophysics. From data collection and context through real-world everyday applications, this book provides an essential resource for anyone involved in oil and gas exploration. Recent and continual advances in machine learning are driving a rapid increase in empirical modeling capabilities. This book shows you how these new tools and methodologies can enhance geophysical and petrophysical data analysis, increasing the value of your exploration data. Apply data-driven modeling concepts in a geophysical and petrophysical context Learn how to get more information out of models and simulations Add value to everyday tasks with the appropriate Big Data application Adjust methodology to suit diverse geophysical and petrophysical contexts Data-driven modeling focuses on analyzing the total data within a system, with the goal of uncovering connections between input and output without definitive knowledge of the system's physical behavior. This multi-faceted approach pushes the boundaries of conventional modeling, and brings diverse fields of study together to apply new information and technology in new and more valuable ways. Enhance Oil & Gas Exploration with Data-Driven Geophysical and Petrophysical Models takes you beyond traditional deterministic interpretation to the future of exploration data analysis.

Pattern Recognition
Pattern Recognition

Author: Katrin Franke

Publisher: Springer

Published: 2006-09-21

Total Pages: 790

ISBN-13: 3540444149

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This book constitutes the refereed proceedings of the 28th Symposium of the German Association for Pattern Recognition, DAGM 2006. The book presents 32 revised full papers and 44 revised poster papers together with 5 invited papers. Topical sections include image filtering, restoration and segmentation, shape analysis and representation, recognition, categorization and detection, computer vision and image retrieval, machine learning and statistical data analysis, biomedical data analysis, and more.