@conference {rizzuti2020EAGEtwri,
	title = {Time-domain wavefield reconstruction inversion for large-scale seismics},
	booktitle = {EAGE Annual Conference Proceedings},
	year = {2020},
	note = {Accepted in EAGE, withdrawn due to logistical challenge},
	month = {1},
	abstract = {Wavefield reconstruction inversion is an imaging technique akin to full-waveform inversion, albeit based on a relaxed version of the wave equation. This relaxation aims to beat the multimodality typical of full-waveform inversion. However it prevents the use of time-marching solvers for the augmented equation and, as a consequence, cannot be straightforwardly employed to large 3D problems. In this work, we formulate a dual version of wavefield reconstruction inversion amenable to explicit time-domain solvers, yielding a robust and scalable inversion technique.},
	keywords = {3D, EAGE, Full-waveform inversion, Time-domain},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2020/rizzuti2020EAGEtwri/rizzuti2020EAGEtwri.html},
	author = {Gabrio Rizzuti and Mathias Louboutin and Rongrong Wang and Felix J. Herrmann}
}
@conference {herrmann2019EAGEHPCaii,
	title = {Accelerating ideation and innovation cheaply in the Cloud the power of abstraction, collaboration and reproducibility},
	booktitle = {4th EAGE Workshop on High-performance Computing},
	year = {2019},
	note = {(EAGE HPC Workshop, Dubai)},
	month = {10},
	keywords = {cloud, devito, EAGE, HPC, JUDI},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/EAGEHPC/2019/herrmann2019EAGEHPCaii/herrmann2019EAGEHPCaii_pres.pdf},
	author = {Felix J. Herrmann and Charles Jones and Gerard Gorman and Jan H{\"u}ckelheim and Keegan Lensink and Paul H. J. Kelly and Navjot Kukreja and Henryk Modzelewski and Michael Lange and Mathias Louboutin and Fabio Luporini and James Selvages and Philipp A. Witte}
}
@conference {witte2017EAGEspl,
	title = {Sparsity-promoting least-squares migration with the linearized inverse scattering imaging condition},
	booktitle = {EAGE Annual Conference Proceedings},
	year = {2017},
	note = {(EAGE, Paris)},
	month = {06},
	abstract = {Reverse-time migration (RTM) with the conventional cross-correlation imaging condition suffers from low-frequency artifacts that result from backscattered energy in the background velocity models. This problem translates to least-squares reverse-time migration (LS-RTM), where these artifacts slow down the convergence, as many of the initial iterations are spent on removing them. In RTM, this problem has been successfully addressed by the introduction of the so-called inverse scattering imaging condition, which naturally removes these artifacts. In this work, we derive the corresponding linearized forward operator of the inverse scattering imaging operator and incorporate this forward/adjoint operator pair into a sparsity-promoting (SPLS-RTM) workflow. We demonstrate on a challenging salt model, that LS-RTM with the inverse scattering imaging condition is far less prone to low-frequency artifacts than the conventional cross-correlation imaging condition, improves the convergence and does not require any type of additional image filters within the inversion. Through source subsampling and sparsity promotion, we reduce the computational cost in terms of PDE solves to a number comparable to conventional RTM, making our workflow applicable to large-scale problems.},
	keywords = {EAGE, imaging condition, least-squares migration, linearized Bregman},
	doi = {10.3997/2214-4609.201701125},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2017/witte2017EAGEspl/witte2017EAGEspl.html},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2017/witte2017EAGEspl/witte2017EAGEspl_poster.pdf},
	author = {Philipp A. Witte and Mengmeng Yang and Felix J. Herrmann}
}
@conference {wason2015EAGEcsm,
	title = {Compressed sensing in 4-D marine{\textendash}-recovery of dense time-lapse data from subsampled data without repetition},
	booktitle = {EAGE Annual Conference Proceedings},
	year = {2015},
	note = {(EAGE, Madrid)},
	month = {06},
	abstract = {We present an extension of our time-jittered marine acquisition for time-lapse surveys by working on more realistic field acquisition scenarios by incorporating irregular spatial grids without insisting on repeatability between the surveys. Since we are always subsampled in both the baseline and monitor surveys, we are interested in recovering the densely sampled baseline and monitor, and then the (complete) 4-D difference from subsampled/incomplete baseline and monitor data.},
	keywords = {EAGE, NFFT, off-the-grid, simultaneous acquisition, time-lapse},
	doi = {10.3997/2214-4609.201413088},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2015/wason2015EAGEcsm/wason2015EAGEcsm.html},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2015/wason2015EAGEcsm/wason2015EAGEcsm_poster.pdf},
	author = {Haneet Wason and Felix Oghenekohwo and Felix J. Herrmann}
}
@conference {esser2015EAGElcs,
	title = {A lifted $\ell_1/\ell_2$ constraint for sparse blind deconvolution},
	booktitle = {EAGE Annual Conference Proceedings},
	year = {2015},
	note = {(EAGE, Madrid)},
	month = {06},
	abstract = {We propose a modification to a sparsity constraint based on the ratio of $\ell_1$ and $\ell_2$ norms for solving blind seismic deconvolution problems in which the data consist of linear convolutions of different sparse reflectivities with the same source wavelet. We also extend the approach to the Estimation of Primaries by Sparse Inversion (EPSI) model, which includes surface related multiples. Minimizing the ratio of $\ell_1$ and $\ell_2$ norms has been previously shown to promote sparsity in a variety of applications including blind deconvolution. Most existing implementations are heuristic or require smoothing the $\ell_1/\ell_2$ penalty. Lifted versions of $\ell_1/\ell_2$ constraints have also been proposed but are challenging to implement. Inspired by the lifting approach, we propose to split the sparse signals into positive and negative components and apply an $\ell_1/\ell_2$ constraint to the difference, thereby obtaining a constraint that is easy to implement without smoothing the $\ell_1$ or $\ell_2$ norms. We show that a method of multipliers implementation of the resulting model can recover source wavelets that are not necessarily minimum phase and approximately reconstruct the sparse reflectivities. Numerical experiments demonstrate robustness to the initialization as well as to noise in the data.},
	keywords = {blind deconvolution, EAGE, EPSI},
	doi = {10.3997/2214-4609.201413420},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2015/esser2015EAGElcs/esser2015EAGElcs.html},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2015/esser2015EAGElcs/esser2015EAGElcs_poster.pdf},
	author = {Ernie Esser and Tim T.Y. Lin and Rongrong Wang and Felix J. Herrmann}
}
@conference {herrmann2014EAGEWSrrt,
	title = {Randomization and repeatability in time-lapse marine acquisition},
	booktitle = {EAGE Workshop on Land and Ocean Bottom; Broadband Full Azimuth Seismic Surveys; Spain},
	year = {2014},
	note = {(EAGE Workshop, Spain)},
	month = {04},
	keywords = {4D seismic, EAGE, Marine acquisition, workshop},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2014/herrmann2014EAGEWSrrt.pdf},
	author = {Haneet Wason and Felix Oghenekohwo and Felix J. Herrmann}
}
@conference {wason2013EAGEobs,
	title = {Ocean bottom seismic acquisition via jittered sampling},
	booktitle = {EAGE Annual Conference Proceedings},
	year = {2013},
	month = {06},
	abstract = {We present a pragmatic marine acquisition scheme where multiple source vessels sail across an ocean-bottom array firing at airgunsjittered source locations and instances in time. Following the principles of compressive sensing, we can significantly impact the reconstruction quality of conventional seismic data (from jittered data) and demonstrate successful recovery by sparsity promotion. In contrast to random (under)sampling, acquisition via jittered (under)sampling helps in controlling the maximum gap size, which is a practical requirement of wavefield reconstruction with localized sparsifying transforms. Results are illustrated with simulations of time-jittered marine acquisition, which translates to jittered source locations for a given speed of the source vessel, for two source vessels.},
	keywords = {Acquisition, blended, deblending, EAGE, interpolation, marine},
	doi = {10.3997/2214-4609.20130379},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2013/wason2013EAGEobs/wason2013EAGEobs.pdf},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2013/wason2013EAGEobs/wason2013EAGEobs_pres.pdf},
	author = {Haneet Wason and Felix J. Herrmann}
}
@conference {herrmann2012EAGEcsm,
	title = {Compressive sensing in marine acquisition and beyond},
	booktitle = {EAGE Annual Conference Proceedings},
	year = {2012},
	month = {06},
	abstract = {Simultaneous-source marine acquisition is an example of compressive sensing where acquisition with a single vessel is replaced by simultaneous acquisition by multiple vessels with sources that fire at randomly dithered times. By identifying simultaneous acquisition as compressive sensing, we are able to design acquisitions that favour recovery by sparsity promotion. Compared to conventional processing that yields estimates for sequential data, sparse recovery leads to significantly improved results for simultaneous data volumes that are collected in shorter times. These improvements are the result of proper design of the acquisition, selection of the appropriate transform domain, and solution of the recovery problem by sparsity promotion. During this talk, we will show how these design principles can be applied to marine acquisition and to other problems in exploration seismology that can benefit from compressive sensing.},
	keywords = {Acquisition, EAGE, marine, workshop},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2012/herrmann2012EAGEcsm/herrmann2012EAGEcsm.pdf},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2012/herrmann2012EAGEcsm/herrmann2012EAGEcsm_pres.pdf},
	url2 = {http://earthdoc.eage.org/publication/publicationdetails/?publication=59854},
	author = {Felix J. Herrmann and Haneet Wason}
}
@conference {wason2012EAGEode,
	title = {Only dither: efficient simultaneous marine acquisition},
	booktitle = {EAGE Annual Conference Proceedings},
	year = {2012},
	month = {06},
	abstract = {Simultaneous-source acquisition is an emerging technology that is stimulating both geophysical research and commercial efforts. The focus here is on simultaneous-source marine acquisition design and sparsity-promoting sequential-source data recovery. We propose a pragmatic simultaneous-source, randomized marine acquisition scheme where multiple vessels sail across an ocean-bottom array firing airguns at {\textendash}- sequential locations and randomly time-dithered instances. Within the context of compressive sensing, where the choice of the sparsifying transform needs to be incoherent with the compressive sampling matrix, we can significantly impact the reconstruction quality, and demonstrate that the compressive sampling matrix resulting from the proposed sampling scheme is sufficiently incoherent with the curvelet transform to yield successful recovery by sparsity promotion. Results are illustrated with simulations of {\textquoteleft}{\textquoteleft}purely" random marine acquisition, which requires an airgun to be located at each source location, and random time-dithering marine acquisition with one and two source vessels. Size of the collected data volumes in all cases is the same. Compared to the recovery from the former acquisition scheme (SNR = 10.5dB), we get good results by dithering with only one source vessel (SNR = 8.06dB) in the latter scheme, which improve at the cost of having an additional source vessel (SNR = 9.44dB).},
	keywords = {Acquisition, EAGE, marine, simultaneous},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2012/wason2012EAGEode/wason2012EAGEode.pdf},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2012/wason2012EAGEode/wason2012EAGEode_pres.pdf},
	url2 = {http://earthdoc.eage.org/publication/publicationdetails/?publication=58915},
	author = {Haneet Wason and Felix J. Herrmann}
}
