Biondo Biondi

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Biondo Biondi
Biondo L. Biondi 2 headshot.png
Latest company Stanford University
BSc Electrical engineering and signal processing
MSc Geophysics
PhD Geophysics
BSc university Politecnico di Milano
MSc university Stanford University
PhD university Stanford University

Biondo L. Biondi graduated from Politecnico di Milano in 1984 and received an M.S. (1988) and a Ph.D. (1990) in geophysics from Stanford, where he is a professor of geophysics. He is co-director of the Stanford Exploration Project (SEP) and leads its efforts in 3D seismic imaging. SEP is an academic consortium whose mission is to develop innovative seismic imaging methodologies and to educate the next generation of leaders in exploration seismology. SEP's activities are supported by approximately 25 companies involved in oil & gas exploration and production. Biondi has made contributions to several aspects of seismic imaging, ranging from velocity estimation to parallel algorithms for seismic migration. Since the early 1990s he has been at the forefront of the development of wave-equation 3D prestack migration methods. In 2004 the Society of Exploration Geophysicists honored Biondi with the Reginald Fessenden Award for his "development of azimuthal moveout (AMO), ... AMO has contributed to many other developments in the areas of migration, multiple attenuation, and regularization of seismic data. During 2007 he gave a one-day short course in 28 cities around the world as the SEG/EAGE Distinguished Instructor Short Course (DISC). Biondi wrote 3D Seismic Imaging[1], the first book to introduce the theory of seismic imaging from the 3D perspective. Biondi is in close contact with the practical applications of seismic imaging by his involvement with 3DGeo Development that he co-founded in 1994. 3DGeo Development is a growing seismic services company that brings innovative technologies to the exploration industry such as wave-equation imaging and Internet-based seismic processing. He is a member of SEG, AGU, EAGE, and SI.

2007 SEG/EAGE Distinguished Instructor Short Course

Concepts and Applications in 3D Seismic Imaging

Seismic images are the basis of crucial exploration, development, and production decisions. Optimal use of these images requires a full understanding of the seismic imaging processes that create them, from data acquisition to the final migration. The primary objective of this course is to provide a broad and intuitive understanding of seismic imaging concepts and methods that enables geoscientists to make the appropriate decisions during acquisition, processing, imaging, and interpretation projects. Another objective is to expose the audience to current trends in imaging research and empower them to adopt new technologies quickly.

The course is organized in four lectures. The first lecture introduces the fundamental concepts of seismic imaging. The remaining lectures focus on the solutions to three crucial problems encountered in practical application of 3D seismic data: 1) choice of the most effective migration algorithm, 2) estimation of the velocity model, and 3) poor image quality caused by irregular and inadequate data spatial sampling and incomplete subsurface illumination.

1. Introduction to 3-D seismic imaging

  • Commonly used data-acquisition geometries and their impact on imaging
  • Seismic imaging as a data focusing process and Kirchhoff migration methods
  • Partial prestack migration and other approximations to full prestack migration
  • Principles of wavefield-continuation equation migration
  • The relationship between seismic velocity and migration

2. A user's guide to the migration toolbox

  • Time vs. depth migration
  • Kirchhoff depth migration
  • Depth migration by wavefield-continuation
  • Anisotropic migration
  • Current trends in depth migration (beam, plane-wave, and reverse-time migration)

3. The never-ending quest for the perfect velocity model

  • Basic methods for velocity estimation (velocity spectra, Dix equation)
  • Velocity estimation and complex structure
  • Principles of reflection traveltime tomography
  • Migration Velocity Analysis (MVA)
  • Introducing geological knowledge in the MVA process
  • Current trends in MVA (velocity scans, residual migration, wave-equation MVA)

4. Imaging, aliasing, and incomplete subsurface illumination

  • Spatial aliasing and imaging artifacts caused by inadequate spatial sampling
  • Avoiding aliasing in Kirchhoff migration and wavefield-continuation migration
  • Imaging artifacts caused by irregular data geometry and incomplete illumination
  • Illumination maps: how to use and not abuse them.
  • Application of approximate regularized inversion to imaging enhancements
    • Data-domain methods (data geometry regularization)
    • Model-domain methods (imaging by least-squares migration)

Additional Resources

The accompanying textbook is available for purchase.[2]

A recording (online streaming version) of this course also is available.[3]

Reginald Fessenden Award 2004

Biondo Biondi is receiving the Reginald Fessenden Award for his development of azimuthal moveout (AMO), which does for 3D data what dip moveout did for 2D data. AMO has contributed to many other developments in the areas of migration, multiple attenuation, and regularization of seismic data. The net result of Biondo's efforts has been an accelerated development of high quality seismic imaging, velocity analysis, and AVO analysis methods in 3D. This work received general recognition in 2001 at an SEG session which Biondi helped organize. In honoring Biondo Biondi, SEG is recognizing the important role that seismic imaging plays in exploration geophysics, and a great innovator in the field.

Biography Citation for the Reginald Fessenden Award

Contributed by Jon Claerbout

Early in his career, Biondo understood that 3D seismology was going to have a major impact on oil and gas exploration and that developing successful 3D algorithms would require much more than simply rewriting 2D equations in 3D.

The azimuth moveout (AMO) process, for which he is being honored, is a perfect example of an inherent 3D process (the AMO operator is capable of transforming both the offset and the azimuth of 3D data) that is particularly useful because of the irregular and incomplete nature of 3D acquisition geometries. AMO is flexible and can interpolate and regularize 3D seismic data. Data need to be regularized because wave-propagation numerical algorithms are more comprehensible and more efficient on a regular grid. A widely used application of AMO is regularizing marine data before common-azimuth migration. This imaging sequence delivers accurate and cost-effective images of the subsurface under complex overburden. Its introduction contributed to the shift toward wave-equation migration for subsalt targets. Since 1993, when he returned to the Stanford Exploration Project (SEP), Biondo has striven to shift SEP research from 2D to 3D. This has led to the development of several algorithms now routinely applied, and to the education of a new generation of seismologists who instinctively look for 3D solutions to seismic imaging problems.

Biondo believes that breakthroughs come only when theoretical ideas are continuously confronted with real 3D data. He therefore began updating SEP's computational infrastructure. SEP needed a powerful computer and had raised the money to buy a Connection Machine 5, the first of a series of parallel computers that turned SEP into a leader of 3D seismology research. An SGI Power Challenge followed and in 1999 we began cluster computing in earnest. Today, SEP boasts about 250 CPUs in our Linux clusters. However, powerful hardware is insufficient without adequate software. Consequently, Biondo set out to design a 3D processing system tailored for algorithmic development. He and Bob Clapp developed SEP3D, a flexible 3D processing system, based on our earlier 2D system called Seplib, that efficiently tested new imaging algorithms on large (by academic standards) 3D data sets.

Biondo's passion for seismology was triggered while working on his honor thesis under Fabio Rocca at the Politecnico di Milano, where he got his diploma in electrical engineering and signal processing in 1984. He became enthusiastic about using creative mathematical approximations and clever algorithms to transform the messy seismic data recorded in the field into beautiful, crisp subsurface images. He subsequently became one of my students at Stanford, where he got his MS (1988) and PhD (1990) in geophysics. Biondo realized that parallel computers would revolutionize our profession. To learn more about this transforming technology, he joined Thinking Machines, a pioneer in parallel computing. He rejoined SEP as a consulting faculty member in 1993, became associate professor (research) of geophysics in 1999, and SEP codirector in 2000.

Biondo's interest in seismic imaging goes beyond new algorithms. He is not fully satisfied unless he sees the algorithm applied to real world problems. To fulfill these practical aspirations, in 1994 he cofounded 3DGeo Development. His ongoing collaboration with 3DGeo provides first-hand experience of the challenges that industry faces when processing large amounts of real data. Thanks to the lessons that Biondo learns through this practical side of his activities, SEP is less in danger of being isolated in the ivory tower of academia.

To share the wealth of knowledge on 3D seismic imaging algorithms accumulated in the past several years, Biondo is working on a textbook 3D Seismic Imaging which will be published by SEG. This is the first book to introduce the theory of seismic imaging from a 3D perspective. It provides an up-to-date and coherent overview of recent progress in 3D wave-equation prestack imaging, many directly achieved, or inspired, by his and his students' work. Biondo and his students are continuing to advance the state-of-the-art in seismic imaging of complex structure.

Particularly promising are recent developments in estimating an accurate velocity function. Biondo and his students have developed methods for extracting velocity information from the results of wave-equation migration and convert this information into velocity updates. Furthermore, they have developed a practical method to use a wave-equation operator to update the velocity. We can thus expect other papers and books that will enrich our knowledge.

References

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