EAGE London: Refining velocity models with tomography and RTM

The talk will take place ONLINE only

Link to the webinar will be provided via e-mails to registered attendees: first e-mail will be sent two days before the event and the second one just 2 hours before the event. Do not register too late!

Agenda (UK time)

18:30-18:35 Introduction and Announcements

18:35-19:20 Refining Velocity Models with Time-Preserving Tomography and RTM Demigration/Migration

19:20-20:00 Q&A +informal discussion

Presenters

Dr. Alan Vigner is a Principal Geophysicist with over 20 years of experience in seismic processing, imaging, and interpretation. Currently serving as a Principal Solution Consultant at AspenTech, he specializes in delivering advanced seismic solutions and training programs. Dr. Vigner has a strong track record in managing large-scale seismic projects and developing innovative Python applications for seismic data analysis. He holds a Ph.D. in Geophysics and has contributed to several publications in the field. His expertise encompasses quantitative interpretation, data integration, and seismic re-processing, with a focus on enhancing subsurface imaging techniques.

Professor Zvi Koren is a Technology Fellow at Aspen Technology and the CTO of its SSE division. He also serves as a visiting professor in the Geophysics Department at Tel Aviv University. Professor Koren earned his Ph.D. in Geophysics from the Department of Geophysics and Planetary Sciences at Tel Aviv University. Following his doctoral studies, he conducted post-doctoral research at the Institute Physique du Globe, Paris University, on seismic inversions (FWI) under the leadership of Professor Albert Tarantola. He then worked as a researcher in the research department of Elf-Aquitaine in Pau, France (1988-1990), focusing on seismic-driven modeling, imaging, and inversion methods. In 1990, he founded the geophysical program at Paradigm, where he led the development of the GeoDepth® system for velocity model building, seismic modeling, and depth imaging. In 2005, he established the EarthStudy 360® product lines, a comprehensive system for high-resolution determination and imaging of subsurface structures and rock material parameters. Throughout his career, Professor Koren has published numerous articles in his areas of expertise and has received several prestigious awards. He is an active member of the SEG and EAGE professional societies.

Talk outline

Achieving accurate seismic depth imaging in geologically complex areas requires more than traditional velocity updates. Two advanced techniques—Time-Preserving Tomography (TPT) and RTM Demigration/Migration—offer a robust and effective workflow to refine velocity models and improve imaging accuracy while maintaining seismic consistency.

Time-Preserving Tomography (TPT) is a model-based method that refines the velocity model while preserving the original seismic traveltimes. This ensures that updates retain kinematic integrity. TPT allows for controlled perturbations in velocity, anisotropy, and depth, resulting in smoother, more geologically consistent models. It is especially effective in complex structural settings, where traditional updates might introduce artifacts or misalignments. By incorporating uncertainty maps, well constraints, and geological knowledge, TPT enhances seismic interpretation and reservoir characterization without compromising traveltime fidelity.

When paired with RTM Demigration/Migration, the benefits of TPT are further enhanced. The workflow begins with a demigration step, where an existing PSDM image (from RTM, Kirchhoff, or ES360) is combined with its velocity model to reconstruct a zero-offset seismic volume. This zero-offset volume can then be remigrated using updated velocity models—such as those refined by TPT—without requiring full pre-stack migrations.

This approach provides a more accurate alternative to vertical stretching or simple depth shifting. It is wave-equation-based, ensuring greater fidelity in structurally complex zones, while also reducing computational cost by avoiding repeated pre-stack imaging.