Enabling affordable omnidirectional subsurface extended image volumes via probing

TitleEnabling affordable omnidirectional subsurface extended image volumes via probing
Publication TypeJournal Article
Year of Publication2017
AuthorsTristan van Leeuwen, Rajiv Kumar, Felix J. Herrmann
JournalGeophysical Prospecting
Volume65
Pagination385-406
Month03
KeywordsAVA, migration velocity analysis, Stochastic optimization
Abstract

Image gathers as a function of subsurface offset are an important tool for the inference of rock properties and velocity analysis in areas of complex geology. Traditionally, these gathers are thought of as multidimensional correlations of the source and receiver wavefields. The bottleneck in computing these gathers lies in the fact that one needs to store, compute, and correlate these wavefields for all shots in order to obtain the desired image gathers. Therefore, the image gathers are typically only computed for a limited number of subsurface points and for a limited range of subsurface offsets, which may cause problems in complex geological areas with large geologic dips. We overcome increasing computational and storage costs of extended image volumes by introducing a formulation that avoids explicit storage and removes the customary and expensive loop over shots found in conventional extended imaging. As a result, we end up with a matrix–vector formulation from which different image gathers can be formed and with which amplitude-versus-angle and wave-equation migration velocity analysis can be performed without requiring prior information on the geologic dips. Aside from demonstrating the formation of two-way extended image gathers for different purposes and at greatly reduced costs, we also present a new approach to conduct automatic wave-equation-based migration-velocity analysis. Instead of focusing in particular offset directions and preselected subsets of subsurface points, our method focuses every subsurface point for all subsurface offset directions using a randomized probing technique. As a consequence, we obtain good velocity models at low cost for complex models without the need to provide information on the geologic dips.

Notes

(Geophysical Prospecting)

URLhttps://slim.gatech.edu/Publications/Public/Journals/GeophysicalProspecting/2016/vanleeuwen2015GPWEMVA/vanleeuwen2015GPWEMVA.pdf
DOI10.1111/1365-2478.12418
Citation Keyvanleeuwen2015GPWEMVA