Seismic time-lapse imaging using interferometric least-squares migration: Case study

Seismic time-lapse surveys are susceptible to repeatability errors due to varying environmental conditions. To mitigate this problem, we propose the use of interferometric least-squares migration to estimate the migration images for the baseline and monitor surveys. Here, a known reflector is used a...

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Bibliographic Details
Published in:Geophysical Prospecting
Main Authors: Sinha, Mrinal, Schuster, Gerard T.
Other Authors: Center for Subsurface Imaging and Fluid Modeling, Earth Science and Engineering Program, Physical Science and Engineering (PSE) Division
Format: Article in Journal/Newspaper
Language:unknown
Published: Wiley 2018
Subjects:
Online Access:http://hdl.handle.net/10754/628819
https://doi.org/10.1111/1365-2478.12684
Description
Summary:Seismic time-lapse surveys are susceptible to repeatability errors due to varying environmental conditions. To mitigate this problem, we propose the use of interferometric least-squares migration to estimate the migration images for the baseline and monitor surveys. Here, a known reflector is used as the reference reflector for interferometric least-squares migration, and the data are approximately redatumed to this reference reflector before imaging. This virtual redatuming mitigates the repeatability errors in the time-lapse migration image. Results with synthetic and field data show that interferometric least-squares migration can sometimes reduce or eliminate artifacts caused by non-repeatability in time-lapse surveys and provide a high-resolution estimate of the time-lapse change in the reservoir. The research reported in this publication was supported by the King Abdullah University of Science and Technology (KAUST) in Thuwal, Saudi Arabia. We thank the sponsors of the CSIM consortium for their support. We would also like to thank the high performance computing (HPC) centre of KAUST for providing access to supercomputing facilities. We would like to thank Statoil (operator of the Norne field) and its license partners ENI and Petoro for the release of the Norne data. Further, we acknowledge the Center for Integrated Operations at NTNU for cooperation and coordination of the Norne Cases.