Simon Shaw

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Simon Shaw
Simon A.Shaw headshot.png


The Karcher Award is being given to Simon A. Shaw in recognition of his contributions in the areas of seismic imaging using inverse scattering series. Simon has worked with imaging the subsurface in areas of complex geology without knowledge of the velocity field. He discovered a subseries that reconstructs earth properties at the proper depth location without requiring accurate information about the background properties of the subsurface. His work further demonstrated the robustness of the process to loss of low-frequency information. Simon has great skill in technical analysis and creative problem solving.


Biography Citation for the J. Clarence Karcher Award

Contributed by Arthur B. Weglein


It is a special pleasure and privilege to write this citation for Simon A. Shaw in honor of his selection for the J. Clarence Karcher Award. This award recognizes his leading and central contribution to the development of a fundamentally new approach to the most serious and significant challenge in current seismic exploration effectiveness: the inability to determine an adequate velocity model under complex geologic circumstances (e.g., salt, basalt and karsted sediments). Under these circumstances, current imaging methods that depend upon an adequate velocity model often fail to produce a satisfactory image. Simon has pioneered a depth accurate imaging method, derived as a subseries of the inverse scattering series. This method deterministically predicts the depth-accurate image without knowing or determining the velocity model, explicitly or implicitly, and without (1) event picking, (2) a moveout trajectory search, and (3) any assumed set of necessary and sufficient conditions satisfied by the image. Simon earned a bachelor’s degree in mechanical engineering from Imperial College in London, a master’s degree in marine studies from the University of Delaware, and a doctorate in geophysics in 2005 from the University of Houston. His career in exploration geophysics began in 1997 when he joined the seismic research group at ARCO in Plano, Texas. Within a year, Simon went from an apprentice position to one with full responsibility for 3D processing projects, an early indication of his ability and potential. Simon engaged with the fundamental research team at ARCO whose members included Doug Foster, Ken Matson, Chuck Mosher, and Dennis Corrigan. After the success of a program to develop new approaches to the removal of free-surface and internal multiples without any subsurface information pioneered by, among others, Paulo Carvalho, Fernanda Araujo, Bob Stolt, and Ken Matson, a new program was initiated to address the outstanding problem of imaging and inverting primaries beneath a complex and ill-defined overburden. The inverse scattering series provided that opportunity, as the only direct multi-D inversion procedure that achieves all the tasks associated with inverse objectives directly in terms of recorded data and an estimate or reference medium properties, which are never assumed to be close to actual, nor adequate, nor ever iterated toward actual properties. Conceptually, velocity independent accurate depth imaging resides within the inverse scattering series. Locating that activity within the series is where Simon Shaw made his mark. He was the first to recognize a pattern that led to a subseries for a leading-order, velocityindependent, depth-imaging algorithm for a 1D medium.

Early numerical tests of the first terms of that imaging subseries appeared unstable, and the Mission-Oriented Seismic Research Program at UH, where Simon was pursuing his PhD, was considering dropping this entire approach to the complex subsurface depth imaging challenge. Simon quietly, courageously, and persistently computed further terms in the imaging subseries, demonstrating that usefulness toward convergence required additional terms. He showed that the earlier computed terms were merely expressing upset with the erroneous input velocity they were given, but were not an indication of its inability to ultimately provide the accurate depth, when more terms in his subseries were included. In fact, that leading-order 1D imaging series was shown to converge for any contrast in velocity, between actual and reference, and subsequently Bob Keys of ExxonMobil provided a closed form that was of important strategic, conceptual, and practical value. Simon extended his 1D method to prestack data and tested it for robustness to random noise and band-limited data. His results gave a green light to our ongoing efforts into the much more complicated, realistic and challenging multidimensional depth-imaging problem.

Simon Shaw is an enormously capable and gifted scientist, and decent human being, and all in his work environment have enjoyed and benefited from those qualities. This J. Clarence Karcher Award recognizes his important contribution, and the role his research played toward solving the problem of depth imaging beneath a complex medium. We fully anticipate and look forward to further high impact scientific and technical contributions from him in the future.