@article {jumah2014GPdre,
	title = {Dimensionality-reduced estimation of primaries by sparse inversion},
	journal = {Geophysical Prospecting},
	volume = {62},
	number = {5},
	year = {2014},
	note = {(Geophysical Prospecting)},
	month = {09},
	pages = {972-993},
	abstract = {Wave-equation based methods, such as the estimation of primaries by sparse inversion, have been successful in the mitigation of the adverse effects of surface-related multiples on seismic imaging and migration-velocity analysis. However, the reliance of these methods on multidimensional convolutions with fully sampled data exposes the {\textquoteleft}curse of dimensionality{\textquoteright}, which leads to disproportional growth in computational and storage demands when moving to realistic 3D field data. To remove this fundamental impediment, we propose a dimensionality-reduction technique where the {\textquoteleft}data matrix{\textquoteright} is approximated adaptively by a randomized low-rank factorization. Compared to conventional methods, which need for each iteration passage through all data possibly requiring on-the-fly interpolation, our randomized approach has the advantage that the total number of passes is reduced to only one to three. In addition, the low-rank matrix factorization leads to considerable reductions in storage and computational costs of the matrix multiplies required by the sparse inversion. Application of the proposed method to two-dimensional synthetic and real data shows that significant performance improvements in speed and memory use are achievable at a low computational up-front cost required by the low-rank factorization.},
	keywords = {factorization, primaries, sparse inversion},
	doi = {10.1111/1365-2478.12113},
	url = {http://onlinelibrary.wiley.com/doi/10.1111/1365-2478.12113/abstract},
	url2 = {https://slim.gatech.edu/Publications/Public/Journals/GeophysicalProspecting/2014/jumah2014GPdre/jumah2014GPdre.pdf},
	author = {Bander Jumah and Felix J. Herrmann}
}
@conference {herrmann2012EAGEpmr,
	title = {Pass on the message: recent insights in large-scale sparse recovery},
	booktitle = {EAGE Annual Conference Proceedings},
	year = {2012},
	month = {06},
	abstract = {Data collection, data processing, and imaging in exploration seismology increasingly hinge on large-scale sparsity promoting solvers to remove artifacts caused by efforts to reduce costs. We show how the inclusion of a "message term" in the calculation of the residuals improves the convergence of these iterative solvers by breaking correlations that develop between the model iterate and the linear system that needs to be inverted. We compare this message-passing scheme to state-of-the-art solvers for problems in missing-trace interpolation and in dimensionality-reduced imaging with phase encoding.},
	keywords = {EAGE, message passing, sparse inversion},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2012/herrmann2012EAGEpmr/herrmann2012EAGEpmr.pdf},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2012/herrmann2012EAGEpmr/herrmann2012EAGEpmr_pres.pdf},
	url2 = {http://earthdoc.eage.org/publication/publicationdetails/?publication=58935},
	author = {Felix J. Herrmann}
}
@conference {vanderneut2012EAGEdecomp,
	title = {Up / down wavefield decomposition by sparse inversion},
	booktitle = {EAGE Annual Conference Proceedings},
	year = {2012},
	month = {06},
	abstract = {Expressions have been derived for the decomposition of multi-component seismic recordings into up- and down-going constituents. However, these expressions contain singularities at critical angles and can be sensitive for noise. By interpreting wavefield decomposition as an inverse problem and imposing constraints on the sparseness of the solution, we arrive at a robust formalism that can be applied to noisy data. The method is demonstrated on synthetic data with multi-component receivers in a horizontal borehole, but can also be applied for different configurations, including OBC and dual-sensor streamers.},
	keywords = {EAGE, sparse inversion, wavefield decomposition},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2012/vanderneut2012EAGEdecomp/vanderneut2012EAGEdecomp.pdf},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2012/vanderneut2012EAGEdecomp/vanderneut2012EAGEdecomp_pres.pdf},
	url2 = {http://earthdoc.eage.org/publication/publicationdetails/?publication=58907},
	author = {Joost van der Neut and Felix J. Herrmann}
}
@conference {lin2011SEGrssde,
	title = {Robust source signature deconvolution and the estimation of primaries by sparse inversion},
	booktitle = {SEG Technical Program Expanded Abstracts},
	volume = {30},
	year = {2011},
	month = {09},
	pages = {4354-4359},
	publisher = {Dept. of Earth and Ocean Sciences, University of British Columbia},
	organization = {Dept. of Earth and Ocean Sciences, University of British Columbia},
	abstract = {The past few years had seen some concentrated interest on a particular wavefield-inversion approach to the popular SRME multiple removal technique called Estimation of Primaries by Sparse Inversion (EPSI). EPSI promises greatly improved tolerance to noise, missing data, edge effect, and other physi- cal phenomenon generally not described by the SRME relation (van Groenestijn and Verschuur, 2009a,b). It is based on the premise that it is possible to stably invert for both the primary impulse response and the source signature despite beforehand having no (or very limited) explicit knowledge of latter. The key to successful applications of EPSI, as shown in very recent works (Savels et al., 2010), is a robust way to reconstruct very sparse primary impulse response events as part of the inversion process. Based on the various successful demonstrations in literature, there is a very strong sense that EPSI will also play an important role in future developments of source sig- nature deconvolution and the general recovering of wavefield spectrum.},
	keywords = {deconvolution, Presentation, Processing, SEG, sparse inversion},
	doi = {10.1190/1.3628116},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/SEG/2011/lin11SEGrssde/lin11SEGrssde.pdf},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/SEG/2011/lin11SEGrssde/lin11SEGrssde_pres.pdf},
	author = {Tim T.Y. Lin and Felix J. Herrmann}
}
