@techreport {slim2014NSERCapp,
	title = {NSERC 2014 DNOISE application},
	number = {TR-EOAS-2014-7},
	year = {2014},
	institution = {UBC},
	abstract = {This current proposal describes a comprehensive five-year continuation of our research project in dynamic nonlinear optimization for imaging in seismic exploration (DNOISE). DNOISE III{\textemdash}Exploration Seismology in the Petascale Age builds on the proven track record of our multidisciplinary research team that conducts transformative research in the fields of seismic-data acquisition, processing, and wave-equation based inversion. The overarching goals of the DNOISE series of projects can be simply summarized as: {\textquoteleft}{\textquoteleft}How to image more deeply and with more detail?" and {\textquoteleft}{\textquoteleft}How to do more with less data?" Also, to help overcome the current substantial challenges in the oil and gas industry, we maintain this focus with more specific follow-up questions such as: {\textquoteleft}{\textquoteleft}How can we control costs and remove acquisition-related artifacts in 3D (time-lapse) seismic data sets?" and {\textquoteleft}{\textquoteleft}How can we replace conventional seismic data processing with wave-equation based inversion, control computational costs, assess uncertainties, extract reservoir information and remove sensitivity to starting models?" To answer these questions, we have assembled an expanded cross-disciplinary research team with backgrounds in scientific computing (SC), machine learning (ML), compressive sensing (CS), hardware design, and computational and observational exploration seismology (ES). With this team, we will continue to drive innovations in ES by utilizing our unparalleled access to high-performance computing (HPC), our expertise and experience in CS and wave-equation based inversion (WEI) and our proven abilities in incorporating our research findings into practical scalable software of our inversion solutions.},
	keywords = {DNOISE, NSERC},
	url = {https://slim.gatech.edu/Publications/Public/TechReport/NSERC/2014/DNOISEIII/crd.html},
	author = {Felix J. Herrmann}
}
@techreport {slim2014NSERCpr,
	title = {NSERC 2014 DNOISE progress report},
	number = {TR-EOAS-2014-8},
	year = {2014},
	institution = {UBC},
	abstract = {As we entered the second half of the DNOISE II project, we are happy to report that we have made significant progress on several fronts. Firstly, our work on seismic data acquisition with compressive sensing is becoming widely recognized. For instance, ConocoPhilips ran a highly successful field trial on Marine acquisition with compressive sensing and obtained significant improvements compared to standard production (see figure below). Moreover, one of the main outcomes of this year{\textquoteright}s EAGE workshop was that industry is ready to adapt randomized sampling as a new acquisition paradigm. Needless to say this is a big success for what we have been trying to accomplish with DNOISE II. Finally, we have made a breakthrough in the application of randomized sampling in 4-D seismic, which is receiving a lot of interest from industry. Secondly, our work on large-scale optimization in the context of wave-equation based inversion is also increasingly widely adapted. For instance, our batching techniques are making the difference between making a loss or profit for a large contractor company active in the area of full-waveform inversion. We also continued to make progress in exciting new directions that go beyond sparsity promotion and which allow us to exploit other types of structure within the data, such as low-rank for matrices or hierarchical Tucker formats for tensors. Application of these techniques show excellent results and in certain cases, such as source separation problems with small dithering, show significant improvements over transform-domain methods. Thirdly, we continued to make significant progress in wave-equation based inversion. We extended our new penalty-based formulation now called Wavefield Reconstruction Inversion/Imaging to include total-variation regularization and density variations. We also continued to make progress on multiples, imaging with multiples and 3-D full-waveform inversion. Statoil is the latest company to join and we have several other companies that have shown a keen interest. We also received substantial in-kind contributions including a license to WesternGeco{\textquoteright}s iOmega and HPC equipment discounts. After many years of support BP decided unfortunately to no longer support SINBAD quoting financial headwind related to the Deep horizon disaster. On a more positive note, we are extremely happy to report major progress on our efforts to secure access to high-performance compute, including renewed funding from NSERC and our involvement in the International Inversion Initiative in Brazil. 9 peer-reviewed journal publications have resulted from our work within the reporting period, with a further 6 submitted, and DNOISE members disseminated the results of our research at 49 major national and international conference presentations. On the HQP training side, 4 MSc students have recently graduated, with one obtaining a position with CGG Calgary, and we added 4 postdocs and 3 PhD students to our team in September 2014, greatly increasing our research capacity. As can be seen from the report below, we are well on schedule and on certain topics well beyond the milestones included in the original proposal. With the purchase of the new cluster we expect to see a surge of activity in extending our algorithms to 3D. With this increased capacity, we continue to be in an excellent position to make fundamental contributions to the fields of seismic data acquisition, processing, and wave-equation based inversion. In the sections below, we give a detailed overview of the research and publication activities of the different members of the group and how these relate to the objectives of the grant, to industrial uptake, and to outreach. Unless stated otherwise the students and PDFs are (co)-supervised by the PI. We refer to the publications section 4.0 for a complete list of our presentations, conference proceedings, and journal publications. We also refer to our mindmap, which clearly establishes connections between the different research topics we have embarked upon as part of the DNOISE II project.},
	keywords = {DNOISE, NSERC},
	url = {https://slim.gatech.edu/Publications/Public/TechReport/NSERC/2014/Progress_Report_2014.html},
	author = {Felix J. Herrmann}
}
@techreport {slim2013NSERCpr,
	title = {NSERC 2013 DNOISE progress report},
	number = {TR-EOAS-2013-5},
	year = {2013},
	institution = {UBC},
	abstract = {As we enter the second half of the DNOISE II project, we are happy to report that we have made significant progress on several fronts. Firstly, our work on seismic data acquisition with compressive sensing is becoming widely recognized, reflected in adaptations of this technology by industry and in this year{\textquoteright}s SEG Karcher award, which went to Gilles Hennenfent, who was one of the researchers who started working in this area in our group. As this report shows, we continued to make progress on this topic with numerous presentations, publications, and software releases. Secondly, our work on large-scale optimization is also widely adapted and instrumental to the different research areas on the grant. In particular, we are excited about new directions that go beyond sparsity promotion and which allow us to exploit other types of structure within the data, such as low-rank. Over the near future, we expect to see a body of new research based on these findings touching acquisition as well as the wave-equation based inversion aspects of our research program. Thirdly, we are also very happy to report that we continued to make substantial progress in wave-equation base inversion. In particular, we would like to mention successes in the areas of acceleration of sparsity-promoting imaging with source estimation and multiples and in theoretical as well as practical aspects of full-waveform inversion. We derived a highly practical and economic formulation of 3-D FWI and we also came up with a complete new formulation of FWI, which mitigates issues related to cycle skipping. Finally, we made a lot of progress applying our algorithm to industrial datasets, which has been well received by industry. Our findings show that FWI is still an immature technology calling for more theoretical input and for the development of practical workflows. Over the last year our work cumulated in 14 peer-reviewed journal publications, 5 submitted journal publications, 13 (+ 9) extended abstracts, 32 talks at international conferences, and 6 software packages. Finally, we are happy to report that we have been joined by several new companies, namely, ION Geophysical, CGG, and Woodside. At this midpoint of the Grant, we are also happy to report that we are well on schedule to meet the milestones included in the original proposal. Given our wide range of expertise and our plans to replace our compute cluster, we continue to be in an excellent position to make fundamental contributions to the fields of seismic data acquisition, processing, and wave-equation based inversion.},
	keywords = {DNOISE, NSERC},
	url = {https://slim.gatech.edu/Publications/Public/TechReport/NSERC/2013/Progress_Report_2013.pdf},
	author = {Felix J. Herrmann}
}
@techreport {slim2012NSERCpr,
	title = {NSERC 2012 DNOISE progress report},
	number = {TR-EOAS-2012-4},
	year = {2012},
	institution = {UBC},
	keywords = {DNOISE, NSERC},
	url = {https://slim.gatech.edu/Publications/Public/TechReport/NSERC/2012/Progress_Report_2012.pdf},
	author = {Felix J. Herrmann}
}
@techreport {slim2011NSERCpr,
	title = {NSERC 2011 DNOISE progress report},
	number = {TR-EOAS-2011-1},
	year = {2011},
	institution = {UBC},
	abstract = {The main thrust of the DNOISE project is focused on the following researth themes: [1] seismic acquisition design and recovery from incomplete data with the goal to reduce acquisition costs while increasing the spatial bandwidth and aperture of seismic data; [2] Removal of the {\textquoteright}surface nonlinearity{\textquoteright} by simultaneous estimation of the source signature and the surface-free Green{\textquoteright}s function by inverting the surface-related multiple prediction operator; [3] Reduction of the computational complexity of full-waveform inversion (FWI) by randomized dimensionality reduction; [4] "Convexification" of FWI to remove or at least diminish the adverse effects of non-uniqueness that has plagued FWI since its inception; The first three themes are directed towards removing major impediments faced by FWI related to the costs of acquiring data, the computational costs of processing and inverting data, and to issues with source calibration and surface-related multiples. The final theme is more {\textquoteright}blue sky{\textquoteright} and tries to incorporate ideas from migration-velocity analysis into the formulation of full-waveform inversion. Aside from these themes, we will continue to work on seismic data acquisition schemes that favor sparsity-promoting recovery and on the development of large-scale solvers using recent developments in convex and stochastic optimization.},
	keywords = {DNOISE, NSERC},
	url = {https://slim.gatech.edu/Publications/Public/TechReport/NSERC/2011/nserc-2011-dnoise-progress-report.pdf},
	author = {Felix J. Herrmann}
}
@techreport {slim2010NSERCapp,
	title = {NSERC 2010 DNOISE application},
	number = {TR-EOAS-2010-3},
	year = {2010},
	institution = {UBC},
	abstract = {DNOISE II: Dynamic Nonlinear Optimization for Imaging in Seismic Exploration is a multidisciplinary research project that involves faculty from the Mathematics, Computer Science, and Earth and Ocean Sciences Departments at the University of British Columbia. DNOISE II constitutes a transformative research program towards a new paradigm in seismic exploration where the acquisition- and processing-related costs are no longer determined by the survey area and discretization but by transform-domain sparsity of the final result. In this approach, we rid ourselves from the confinements of conventional overly stringent sampling criteria that call for regular sampling with sequentiual sources at Nyquist rates. By adapting the principles of compressive sensing, DNOISE II promotes a ground-up formulation for seismic imaging where adverse subsampling-related artifacts are removed by intelligent simultaneous-acquisition design and recovery by transform-domain sparsity promotion. This development{\textendash}-in conjunction with our track records in sparse recovery and time-harmonic Helmholtz solvers{\textendash}-puts us in an unique position to deliver on fundamental breakthroughs in the development and implementation of the next-generation of processing, imaging, and full-waveform inversion solutions.},
	keywords = {DNOISE, NSERC},
	url = {https://slim.gatech.edu/Publications/Public/TechReport/NSERC/2010/nserc-2010-dnoise-application.pdf},
	author = {Felix J. Herrmann}
}
