# Efficient least-squares migration with sparsity promotion

 Title Efficient least-squares migration with sparsity promotion Publication Type Conference Year of Publication 2011 Authors Felix J. Herrmann, Xiang Li Conference Name EAGE Annual Conference Proceedings Month 05 Organization EAGE Keywords EAGE, Imaging, Presentation Abstract Seismic imaging relies on the collection of multi-experimental data volumes in combination with a sophisticated back-end to create high-fidelity inversion results. While significant improvements have been made in linearized inversion, the current trend of incessantly pushing for higher quality models in increasingly complicated regions reveals fundamental shortcomings in handling increasing problem sizes numerically. The so-called curse of dimensionality" is the main culprit because it leads to an exponential growth in the number of sources and the corresponding number of wavefield simulations required by wave-equation" migration. We address this issue by reducing the number of sources by a randomized dimensionality reduction technique that combines recent developments in stochastic optimization and compressive sensing. As a result, we replace the cur- rent formulations of imaging that rely on all data by a sequence of smaller imaging problems that use the output of the previous inversion as input for the next. Empirically, we find speedups of at least one order-of-magnitude when each reduced experiment is considered theoretically as a separate compressive-sensing experiment. URL https://www.slim.eos.ubc.ca/Publications/Public/Conferences/EAGE/2011/herrmann11EAGEefmsp/herrmann11EAGEefmsp.pdf Presentation https://www.slim.eos.ubc.ca/Publications/Public/Conferences/EAGE/2011/he... URL1 http://earthdoc.eage.org/publication/publicationdetails/?publication=50333 Citation Key herrmann2011EAGEefmsp