Seismic Data Interpretation using Digital Image Processing (Hardcover)

Bridging the gap between modern image processing practices by the scientific community at large and the world of geology and reflection seismology

This book covers the basics of seismic exploration, with a focus on image processing techniques as applied to seismic data. Discussions of theories, concepts, and algorithms are followed by synthetic and real data examples to provide the reader with a practical understanding of the image processing technique and to enable the reader to apply these techniques to seismic data. The book will also help readers interested in devising new algorithms, software and hardware for interpreting seismic data.

Key Features:

• Provides an easy to understand overview of popular seismic processing and interpretation techniques from the point of view of a digital signal processor.
• Presents image processing concepts that may be readily applied directly to seismic data.
• Includes ready-to-run MATLAB algorithms for most of the techniques presented.

The book includes essential research and teaching material for digital signal and image processing individuals interested in learning seismic data interpretation from the point of view of digital signal processing. It is an ideal resource for students, professors and working professionals who are interested in learning about the application of digital signal processing theory and algorithms to seismic data.

ABDULLATIF A. AL-SHUHAIL is an Associate Professor of Geophysics at King Fahd University of Petroleum & Minerals (KFUPM). He got his BS from KFUPM in Geophysics in 1988, his MS and PhD in Geophysics from Texas A&M University at College Station in 1993 and 1998, respectively. Since then he has been teaching and advising at KFUPM. He founded and directed the Near Surface Seismic Investigation Consortium at KFUPM in 2006-2008. He has authored and co-authored several papers in the field of petroleum seismic exploration. He is an active member of the Society of Exploration Geophysicists, the European Association of Geoscientists & Engineers, and the Dhahran Geoscience Society. His interests include near-surface effects on petroleum seismic data, seismic investigation of fractured reservoirs, and ground penetrating radar.

SALEH A. AL-DOSSARY works in the Exploration Application Services Department in Saudi Aramco Oil Company, developing new seismic processing, attributes and pre-stack depth-migration algorithms. In 1991, Saleh received his B.S. degree in Computer Science with a minor in Geophysics from the New Mexico Institute of Mining and Technology, Socorro, NM. He received his M.S. degree in 1997 from Stanford University, Palo Alto, CA, and in 2004 he received his Ph.D. from the University of Houston, TX, both in Geophysics. Saleh holds five patents, and is an applicant for five additional patents in seismic edge preserving and detection technology. He is the author and coauthor of several articles published by the Society of Exploration Geophysicists (SEG). Saleh received the Distinguished Employee Award in Saudi Aramco's Exploration Application Services Department in 1999, the Outstanding Student Award from the University of Houston in 2003 and the Saudi Aramco Excellence Award in 2015.

WAIL A. MOUSA is an Associate Professor with the Electrical Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM). He received the B.Sc. degrees in electrical engineering and mathematical sciences and M.Sc. degree in electrical engineering from KFUPM, in 2000, 2001, and 2003, respectively, and the Ph.D. degree in electronics and electrical engineering from the University of Leeds in 2006. Between 2003 and 2009, he worked as a Research Scientist on applied signal processing for geology and geophysics at the Schlumberger. His research interests include digital signal processing and its application in geophysics, with particular emphasis on Seismic Data Processing. Additional interests include design and implementation of digital filters including wavefield extrapolation filters, image segmentation, pattern recognition, and classification and their applications related to geophysical and geological data.