EAGE London Evening Talk
Understanding uncertainty in velocity model building through pseudo-random big data analysis is the title of Tony Martin's talk at this EAGE evening lecture in London. The event takes place at Imperial College, Royal School of Mines in Kensington.
Tony Martin works for PGS in the role of Principal Geophysicist. He has 25 years of industry experience working for both contractors and operators and has worked in various locations around the world. He has been published on more than 25 occasions. He is a member of the EAGE, SEG and an Associate Editor for Geophysics.
Velocity model building using a tomographic inversion engine produces one credible realization of an earth model, generating one plausible sub-surface image. The inversion attempts to minimize the difference between the unknown true model and a best-guess version; by its nature it is highly non-linear, leading to uncertainty in the traditional single model and image approach. A methodology for reducing uncertainty is to use a significant model population that all equally explain the data by producing flat gathers from a tomographic inversion. This big data approach to imaging can follow a pseudo-random approach, enabling statistically driven error bar analysis on the spatial reliability of the data.