@conference {herrmann2014CSEGbsw,
	title = {Breaking structure - why randomized sampling matters},
	booktitle = {CSEG Technical Luncheon},
	year = {2014},
	month = {01},
	abstract = {During this talk, I will explain how ideas from compressive sensing and big data can be used to reduce costs of seismic data acquisition and wave-equation based inversion. The key idea is to explore structure within the data by deliberately breaking this structure with randomized sampling, e.g., by randomizing source/receiver positions or by source encoding, followed by an optimization procedure that restores the structure and therefore recovers the fully sampled data. These techniques not only underpin recent advances in missing trace interpolation and simultaneous acquisition but they are also responsible for significant improvements in full-waveform inversion and reverse-time migration. We will illustrate these concepts using a variety of compelling examples on realistic synthetics and field data.},
	keywords = {CSEG, randomized sampling},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/CSEG/2014/herrmann2014CSEGbsw_pres.pdf},
	author = {Felix J. Herrmann}
}
@article {shahidi2013GPars,
	title = {Application of randomized sampling schemes to curvelet-based sparsity-promoting seismic data recovery},
	journal = {Geophysical Prospecting},
	volume = {61},
	number = {5},
	year = {2013},
	month = {09},
	pages = {973-997},
	abstract = {Reconstruction of seismic data is routinely used to improve the quality and resolution of seismic data from incomplete acquired seismic recordings. Curvelet-based Recovery by Sparsity-promoting Inversion, adapted from the recently-developed theory of compressive sensing, is one such kind of reconstruction, especially good for recovery of undersampled seismic data. Like traditional Fourier-based methods, it performs best when used in conjunction with randomized subsampling, which converts aliases from the usual regular periodic subsampling into easy-to-eliminate noise. By virtue of its ability to control gap size, along with the random and irregular nature of its sampling pattern, jittered (sub)sampling is one proven method that has been used successfully for the determination of geophone positions along a seismic line. In this paper, we extend jittered sampling to two-dimensional acquisition design, a more difficult problem, with both underlying Cartesian, and hexagonal grids. We also study what we term separable and non-separable two-dimensional jittered samplings. We find hexagonal jittered sampling performs better than Cartesian jittered sampling, while fully non-separable jittered sampling performs better than separable jittered sampling. Two other 2D randomized sampling methods, Poisson Disk sampling and Farthest Point sampling, both known to possess blue-noise spectra, are also shown to perform well.},
	keywords = {curvelets, Geophysical Prospecting, randomized sampling},
	doi = {10.1111/1365-2478.12050},
	url = {https://slim.gatech.edu/Publications/Public/Journals/GeophysicalProspecting/2013/shahidi2013GPars/shahidi2013GPars.pdf},
	author = {Reza Shahidi and Gang Tang and Jianwei Ma and Felix J. Herrmann}
}
@article {mansour2013GEOPiwr,
	title = {Improved wavefield reconstruction from randomized sampling via weighted one-norm minimization},
	journal = {Geophysics},
	volume = {78},
	number = {5},
	year = {2013},
	month = {08},
	pages = {V193-V206},
	abstract = {Missing-trace interpolation aims to recover the gaps caused by physical obstacles or deliberate subsampling to control acquisition costs in otherwise regularly sampled seismic wavefields. Although transform-domain sparsity promotion has proven to be an effective tool to solve this recovery problem, current recovery techniques do not fully utilize a priori information derived from the locations of the transform-domain coefficients, especially when curvelet domain sparsity is exploited. We use recovery by weighted one-norm minimization, which exploits correlations between the locations of significant curvelet coefficients of different partitions, e.g., shot records, common-offset gathers, or frequency slices of the acquired data. We use these correlations to define a sequence of 2D curvelet-based recovery problems that exploit 3D continuity exhibited by seismic wavefields without relying on the highly redundant 3D curvelet transform. To test the performance of our weighted algorithm, we compared recoveries from different data sorting and partitioning scenarios for a seismic line from the Gulf of Suez. These tests demonstrated that our method is superior to standard $\ell_1$ minimization in terms of antialiasing capability, reconstruction quality and computational memory requirements.},
	keywords = {compressed sensing, randomized sampling, Trace interpolation, weighted one-norm minimization},
	doi = {10.1190/geo2012-0383.1},
	url = {https://slim.gatech.edu/Publications/Public/Journals/Geophysics/2013/mansour2013GEOPiwr/mansour2013GEOPiwr.pdf},
	author = {Hassan Mansour and Felix J. Herrmann and Ozgur Yilmaz}
}
@conference {herrmann2013SPIErse,
	title = {Randomized sampling in exploration seismology},
	booktitle = {SPIE Optics and Photonics: Wavelets and Sparsity XV},
	year = {2013},
	month = {08},
	keywords = {Exploration seismology, randomized sampling, SPIE},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/SPIE/2013/herrmann2013SPIErse/herrmann2013SPIErse_pres.pdf},
	author = {Felix J. Herrmann}
}
@conference {herrmann2013KAUSTrse,
	title = {Randomized sampling in exploration seismology},
	booktitle = {KAUST},
	year = {2013},
	month = {05},
	publisher = {KAUST},
	organization = {KAUST},
	keywords = {Exploration seismology, KAUST, randomized sampling},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/KAUST/2013/herrmann2013KAUSTrse/herrmann2013KAUSTrse_pres.pdf},
	author = {Felix J. Herrmann}
}
@conference {herrmann2013SEGOMANrdw,
	title = {Recent developments in wave-equation based inversion technology},
	booktitle = {SEG Workshop on FWI; Oman},
	year = {2013},
	month = {04},
	keywords = {3D, Exploration seismology, FWI, randomized sampling, SEG, workshop},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/SEG/2013/herrmann2013SEGOMANrdw/herrmann2013SEGOMANrdw_pres.pdf},
	author = {Felix J. Herrmann}
}
