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Seismic imaging methods are currently used to produce images of the Earth's subsurface properties at diverse length scales, from high-resolution, near-surface environmental studies for oil and gas exploration to long-period images of the entire planet. This book presents the physical and mathematical basis of imaging algorithms in the context of controlled-source reflection seismology. The approach taken is motivated by physical optics and theoretical seismology. The theory is constantly put into practice via a graded sequence of computer exercises using the widely available SU (Seismic Unix) software package.
Describes the use of inverse scattering theory in seismic imaging for seismic processing practitioners and theoretical geophysicists.
Covering ideas and methods while concentrating on fundamentals, this book includes wave motion; digital imaging; digital filtering; visualization aspects of the seismic reflection method; sampling theory; the frequency spectrum; synthetic seismograms; wavelet processing; deconvolution; seismic attributes; phase rotation; and seismic attenuation.
This book describes the theory and practice of inverting seismic data for the subsurface rock properties of the earth. The primary application is for inverting reflection and/or transmission data from engineering or exploration surveys, but the methods described also can be used for earthquake studies. Seismic Inversion will be of benefit to scientists and advanced students in engineering, earth sciences, and physics. It is desirable that the reader has some familiarity with certain aspects of numerical computation, such as finite-difference solutions to partial differential equations, numerical linear algebra, and the basic physics of wave propagation. For those not familiar with the terminology and methods of seismic exploration, a brief introduction is provided. To truly understand the nuances of seismic inversion, we have to actively practice what we preach (or teach). Therefore, computational labs are provided for most of the chapters, and some field data labs are given as well.
The use of diffraction imaging to complement the seismic reflection method is rapidly gaining momentum in the oil and gas industry. As the industry moves toward exploiting smaller and more complex conventional reservoirs and extensive new unconventional resource plays, the application of the seismic diffraction method to image sub-wavelength features such as small-scale faults, fractures and stratigraphic pinchouts is expected to increase dramatically over the next few years. “Seismic Diffraction” covers seismic diffraction theory, modeling, observation, and imaging. Papers and discussion include an overview of seismic diffractions, including classic papers which introduced the potential of diffraction phenomena in seismic processing; papers on the forward modeling of seismic diffractions, with an emphasis on the theoretical principles; papers which describe techniques for diffraction mathematical modeling as well as laboratory experiments for the physical modeling of diffractions; key papers dealing with the observation of seismic diffractions, in near-surface-, reservoir-, as well as crustal studies; and key papers on diffraction imaging.
Providing a pictorial presentation of the basic principles of Kirchhoff-type imaging and proceeding to a comprehensive treatment of its kinematic and dynamic aspects, this book is a valuable addition for anyone interested in the theory and practices of seismic data processing for imaging and parameter estimation with all its attendant processes.
For more than 80 years, the oil and gas industry has used seismic methods to construct images and determine physical characteristics of rocks that can yield information about oil and gas bearing structures in the earth. This book presents the different seismic data processing methods, also known as seismic "migration," in a unified mathematical way. The book serves as a bridge between the applied math and geophysics communities by presenting geophysicists with a practical introduction to advanced engineering mathematics, while presenting mathematicians with a window into the world of the mathematically sophisticated geophysicist.
Seismic Imaging Methods and Application for Oil and Gas Exploration connects the legacy of field data processing and imaging with new research methods using diffractions and anisotropy in the field of geophysics. Topics covered include seismic data acquisition, seismic data processing, seismic wave modeling, high-resolution imaging, and anisotropic modeling and imaging. This book is a necessary resource for geophysicist working in the oil and gas and mineral exploration industries, as well as for students and academics in exploration geophysics. Provides detailed methods that are used in the industry, including advice on which methods to use in specific situations Compares classical methods with the latest technologies to improve practice and application in the real world Includes case studies for further explanation of methods described in the book
This second volume provides a foundation for understanding the vigorous, relevant, and fascinating field of seismic processing, addressing that portion which precedes migration. Written for the non-expert, this second volume of the two-volume introductory text reveals the limitations and potential pitfalls of seismic data, prepares both seismic interpreters and acquisition specialists for working with seismic processing geophysicists, explains seismic processing operations as a series of solutions to problems, and demonstrates the dependence of a final interpretable seismic volume on its many seismic processing decisions. Although seismic processing is inherently mathematical, this text uses numerous illustrations and real data examples, providing an intuitive understanding of the seismic processing procedures and resorting to an algebra-based argument only on rare occasions. The first volume starts with migration. This second volume addresses pre-migration processing. In combination, these two volumes present seismic processing topics in order reverse of a typical processing sequence. Through this reverse ordering, the reader understands an algorithm's input requirements, providing motivation for understanding the preceding algorithm in the processing sequence.