HR: 1340h
AN: S33A-1083    [Abstracts]
TI: Depth Migration Comparison to Waveform Tomography from a high Resolution 3D Seismic Dataset
AU: * Fradelizio, G
EM: gluigi@rice.edu
AF: Dept of Earth Science-Rice University MS 126, 6100 Main St., Houston, TX 77005
AU: Levander, A
AF: Dept of Earth Science-Rice University MS 126, 6100 Main St., Houston, TX 77005
AU: Zelt, C A
AF: Dept of Earth Science-Rice University MS 126, 6100 Main St., Houston, TX 77005
AU: Gao, F
AF: Dept of Earth Science-Rice University MS 126, 6100 Main St., Houston, TX 77005
AB: The accuracy of shallow environmental seismic images as input for quantitative groundwater and engineering studies strongly relies on the accuracy and detail of the velocity model used in processing, to map the structural features and predict depth and layer thickness. However, conventional NMO velocity analysis can be non-trivial in shallow reflection profiles, due to coherent noise often present in the data and poor signal resolution, associated with a limited range of offsets. Furthermore, the inherent assumption of horizontal reflectors may be erroneous or break down because of large velocity contrasts and lateral heterogeneities, leading to an incorrect depth profile based on Dix's equation. Different methods exist to improve interval velocity estimates; here we present a comparison of migrated images from a 3D seismic reflection dataset at a contaminated site obtained using conventional NMO velocity analysis, stack, inversion of the NMO velocity field and migration, versus depth migrated images obtained using travel time and waveform tomography velocity models. Inverse methods, in fact, provide a powerful tool to build a relatively complex velocity model in depth that is very close to the migration velocity model, and has the advantages of eliminating a number of processing steps and avoiding the depth conversion approximation. Another advantage over more processing oriented methods is that the velocity field provided is often sufficiently accurate without further fine-tuning through iterative profile migrations, which can be difficult to perform in poor signal resolution datasets. Although pre-stack depth migration is the most accurate and detailed imaging method, post-stack depth migration can often produce an acceptable image if an accurate and detailed depth-velocity model is used and the structures are not extremely complex.
DE: 7260 Theory and modeling
DE: 7294 Instruments and techniques
DE: 7203 Body wave propagation
SC: Seismology [S]
MN: 2004 AGU Fall Meeting