A comparison between imaging results in a complex salt environment, offshore Gulf of Mexico. Conventional reverse time migration (RTM), after pre-processing & regularisation versus DUG MP-FWI Imaging result using field-data input. Superior resolution. Superior imaging. (Data courtesy of Shell)
A section and depth slice through a conventional processed Kirchhoff image versus DUG MP-FWI Imaging. MP-FWI delivers a clear resolution increase thanks to the full-wavefield least-squares imaging. (BEX MC3D data courtesy of Multi-Client Resources)
A depth slice through a conventional processed Kirchhoff image versus DUG MP-FWI Imaging. MP-FWI delivers a clear resolution increase thanks to the full-wavefield least-squares imaging. (BEX MC3D data courtesy of Multi-Client Resources)
The initial velocity model and FWI updated model in 3D. Note the clear increase in detail introduced by FWI. (BEX MC3D data courtesy of Multi-Client Resources)
MP-FWI Imaging can simultaneously estimate a high-frequency, true-amplitude reflectivity (top) & an accurate velocity model (bottom) using raw field data. Complex geological features are resolved through the novel, iterative least-squares, multi-scattering inversion. (BEX MC3D data courtesy of Multi-Client Resources)
Obtain unrivalled results faster with our Multi-parameter FWI (MP-FWI) Imaging technology. Simultaneous model building and high-frequency, least-squares imaging deliver accurate, high-resolution Earth models using field-data input—without the many time-consuming, subjective, serial steps of a conventional processing and imaging workflow. At high frequency, this revolutionary approach provides reflectivity images for both structural and quantitative interpretation, including angle stacks for AVA analysis.
FWI inverts for high-resolution earth models using the entire seismic wavefield. It is an integral part of our depth model-building strategies for conventional imaging workflows.
Starting velocity model and final model after FWI. Depth slice and inline with migrated stack overlaid with the respective velocity model. In this OBN example the shallow channels are well resolved after FWI, correcting the imaging distortions at depth. (Data courtesy of Carbon Transition and TGS)
Before and after FWI. Smooth starting velocity model prior to FWI (left) and after FWI, co-rendered with the seismic data (right). (Data courtesy of Shell NZ).
FWI using both high-resolution streamer data and sparse OBN data. Velocity updates beyond 5 km depth are achieved thanks to the long offset diving wave penetration of the OBN data. (LumiSeisTM data courtesy of MCG)
Designed for geoscience, not computer science. Backed by some of the greenest HPC on the planet.
Diving wave penetration QC. The white “bananas” demonstrate the maximum depth of update expected from diving wave FWI.
