@article {sharan2018fsp,
	title = {Fast sparsity-promoting microseismic source estimation},
	journal = {Geophysical Journal International},
	volume = {216},
	number = {1},
	year = {2019},
	note = {(Geophysical Journal International)},
	month = {01},
	pages = {164-181},
	abstract = {Microseismic events are generated during hydraulic fracturing of unconventional reservoirs and carry information on fracture locations and the origin times associated with these microseismic events. For drilling purposes and to prevent hazardous situations, we need to have accurate knowledge on the fracture locations as well as on their size, and their density. Because microseismic waves can travel far distances, microseismic data collected at the surface and or in boreholes can help us to monitor hydraulic fracturing. While so-called back propagation or time-reversal methods are able to focus recorded energy back onto the sources when a reasonable velocity model is available, these methods suffer from blurring especially in situations where the data acquisition suffers from lack of aperture, sparse sampling, and noise. As a result, these methods typically cannot resolve sources in close proximity, a desired feature since we need this information if we want to follow the fracture evolution in space and time. In that situation, we need to estimate the locations and the associated source-time functions for closely spaced microseismic sources along the active fractures. To overcome the limitations of time-reversal methods, we propose a wave-equation based inversion approach where we invert for the complete source wavefield in both space and time. By promoting sparsity on the source wavefield in space, we negate the effects of non-radiating sources during the inversion and obtain high-resolution intensity plots and high-fidelity estimates for the source-time functions. We obtain these results relatively fast by accelerating the linearized Bregman method with a dual formulation. Through experiments, we demonstrate that our method is computationally feasible, robust to noise, and works for closely spaced sources with overlapping source-time functions in complex geological settings.},
	keywords = {induced seismicity, Joint inversion, waveform inversion},
	doi = {10.1093/gji/ggy415},
	url = {https://slim.gatech.edu/Publications/Public/Journals/GeophysicalJournalInternational/2018/sharan2018fsp/sharan2018fsp.pdf},
	author = {Shashin Sharan and Rongrong Wang and Felix J. Herrmann}
}
@conference {wang2016SEGfde,
	title = {Frequency down-extrapolation with TV norm minimization},
	booktitle = {SEG Technical Program Expanded Abstracts},
	year = {2016},
	note = {(SEG, Dallas)},
	month = {10},
	pages = {1380-1384},
	abstract = {In this work, we present a total-variation (TV)-norm minimization method to perform model-free low-frequency data extrapolation for the purpose of assisting full-waveform inversion. Low-frequency extrapolation is the process of extending reliable frequency bands of the raw data towards the lower end of the spectrum. To this end, we propose to solve a TV-norm based convex optimization problem that has a global minimum and is equipped with a fast solver. The approach takes into account both the sparsity of the reflectivity series associated with a single trace, as well as the inter-trace correlations. A favorable byproduct of this approach is that it allows one to work with coarsely sampled trace along time (as coarse as 0.02s per sample), hence substantially reduces the size of the proposed optimization problem. Last, we show the effectiveness of the method for frequency-domain FWI on the Marmousi model.},
	keywords = {extrapolation, FWI, SEG, sparse},
	doi = {10.1190/segam2016-13879674.1},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/SEG/2016/wang2016SEGfde/wang2016SEGfde.html},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/SEG/2016/wang2016SEGfde/wang2016SEGfde_pres.pdf},
	author = {Rongrong Wang and Felix J. Herrmann}
}
@techreport {wang2014SEGfwi,
	title = {Full waveform inversion with interferometric measurements},
	number = {TR-EOAS-2014-5},
	year = {2014},
	month = {04},
	institution = {UBC},
	abstract = {In this note, we design new misfit functions for full-waveform inversion by using interferometric measurements to reduce sensitivity to phase errors. Though established within a completely different setting from the linear case, we obtain a similar observation: the interferometry can improve robustness under certain modeling errors. Moreover, in order to deal with errors on both source and receiver sides, we propose a higher order interferometry, which, as a generalization of the usual definition, involves the cross correlation of four traces. A proof of principle simulations is included on a stylized example.},
	keywords = {FWI},
	url = {https://slim.gatech.edu/Publications/Public/TechReport/2014/wang2014SEGfwi/wang2014SEGfwi.html},
	author = {Rongrong Wang and Ozgur Yilmaz and Felix J. Herrmann}
}
