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Welcome to my short series of "Lectures on Full Waveform Inversion". In this lecture, I will give an overview of the course and recommend lecture notes, tutorials, FWI software, as well as general lectures on numerical optimization. The short series "Lectures on FWI" is part of the "Inverse Theory" course in the masters program "Geophysics" at Christian-Albrechts-University Kiel.
Adrian Umpleby, Imperial College - London Directors: Liacir Lucena, Universidade Federal do Rio Grande do Norte (Brazil) Mike Warner, Imperial College London (UK) Felix J. Herrmann, University of British Columbia (Canada) Full waveform inversion (FWI) is now a widely established theory of geophysical imaging, yet not fully applied in practise due to limitations of seismic acquisitions, seismic simulations, inversion algorithms, and computational restrictions. This workshop will explore theoretical and practical applications of FWI theory through a series of Tutorials using field datasets, and Lectures discussing current leading industry practise, the latest research developments on theoretical and computational fronts, and techniques of data preconditioning and computational optimization. Researchers, students and industry practitioners are invited to attend.
Welcome back to my short series of "Lectures on Full Waveform Inversion". In this lecture, I will review the basic theoretical concept of seismic FWI. The short series "Lectures on FWI" is part of the "Inverse Theory" course in the masters program "Geophysics" at Christian-Albrechts-University Kiel.
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In this E-Lecture: "FWI with optimal transport: a 3D implementation and an application on a field dataset", we present the application to a 3D real dataset of full waveform inversion (FWI) with optimal transport (OT) using the Kantorovich-Rubinstein (KR) distance as proposed by Métivier et al. (2016). This approach involves an efficient numerical implementation for OT in time and space directions, allowing the lateral coherency of the traces to be taken into account; this has an important impact on the quality of the results. The approach also exhibits a reduced sensitivity to local minima compared to least squares (LSQ) misfit. Moreover the iterative method used for the computation of the KR distance allows the production of a set of intermediary solutions that span progressively from LSQ to OT. We recall the main components of the approach and present its numerical implementation in 3D. We show the improvement of the results compared to LSQ FWI on real datasets.
Wide-azimuth long-offset OBC/OBN surveys provide a suitable framework to perform computationally-efficient 3D frequency-domain full waveform inversion (FWI) with a few discrete frequencies. Frequency-domain seismic modeling is performed efficiently with moderate computational resources for a large number of seismic sources with the sparse multifrontal direct solver MUMPS. The relevance and the computational efficiency of the frequency-domain FWI performed in the visco-acoustic VTI approximation is shown with a real 3D OBC case study from the North Sea. The subsurface models built by FWI show a dramatic resolution improvement relative to the initial model built by reflection traveltime tomography down to the base cretaceous reflector below the reservoir level. The relevance of the FWI model is assessed by frequency-domain and time-domain seismic modellings and source wavelet estimation, which might reveal the footprint of attenuation on the imaging results. This video is part of EAGE Online Education Programme. The European Association of Geoscientists and Engineers (EAGE) is a global professional, non-profit association for geoscientists and engineers. EAGE strives to promote innovation and technical progress and aims to foster communication and cooperation between those working in, studying or interested in these fields. To learn more about EAGE Education visit 🤍LearningGeoscience.org
DEFORESTASI TANPA HENTI DI INDONESIA Presiden Republik Indonesia, Joko Widodo, mengakui bahwa Indonesia merupakan penyumbang emisi karbon terbesar keenam di dunia. Pada tahun 2011 Pemerintah Indonesia mengeluarkan Peraturan Presiden No. 61/2011 mengenai Rencana Aksi Nasional Penurunan Emisi Gas Rumah Kaca 2010-2020. Kemudian juga Indonesia meratifikasi Paris Agreement dengan Undang-undang No. 16 tahun 2016 tentang Pengesahan Paris Agreement to the United Nations Framework Convention on Climate Change. Indonesia berkomitmen mengurangi emisi sebesar 29% dengan upaya sendiri dan menjadi 41% jika ada kerja sama internasional dari kondisi tanpa ada aksi (business as usual) pada tahun 2030, salah satunya melalui sektor kehutanan dan pertanian. Indonesia tidak akan mencapai target pengurangan emisi yang telah ditetapkannya sendiri itu tanpa mengatasi deforestasi dan degradasi hutan. Fakta menunjukkan bahwa sejarah kehutanan Indonesia tak lain adalah sejarah deforestasi, dari dulu hingga kini. Analisis FWI dan GFW tahun 2001 memperlihatkan bahwa laju deforestasi terus meningkat, menjadi 2 juta hektare/tahun periode 1996-2000. Selanjutnya menjadi 1,5 juta hektare/tahun periode 2001-2010 dan periode 2009-2013 lajunya sebesar 1,1 juta hektare/tahun (FWI, 2011 & 2014). Kajian terbaru FWI, walaupun hanya dipotret pada 3 provinsi, laju deforestasi masih relatif tinggi, yaitu sekitar 240 ribu hektare/tahun periode 2013-2016, meningkat dibanding periode sebelumnya (2009-2013), yaitu sekitar 146 ribu hektare/tahun. Bila ditotal maka hutan alam yang ada di Sumatera Utara, Kalimantan Timur, dan Maluku Utara, telah hilang seluas 718 ribu hektare selama tiga tahun. Hasil analisis lainnya ditemukan sekitar 72% deforestasi yang terjadi di 3 provinsi tersebut berada di dalam wilayah yang telah dibebani izin pengelolaan. Aktivitas-aktivitas di dalam konsesi HPH, HTI, perkebunan kelapa sawit dan pertambangan menjadi penyebab langsung (direct causes) deforestasi. Peningkatan laju deforestasi terjadi di Provinsi Maluku Utara dan Kalimantan Timur meningkat signifikan, dibandingkan apa yang terjadi di Sumatera Utara. Di Maluku Utara, peningkatan laju deforestasi bahkan mencapai lebih dari dua kali lipat jika dibandingkan dengan periode sebelumnya, dari 25 ribu hektare/tahun menjadi 52 ribu hektare/tahun. Begitu juga halnya dengan Kalimantan Timur dimana laju deforestasi meningkat hampir dua kali lipat dari periode sebelumnya, dari 84 ribu hektare/tahun di tahun 2013 menjadi 157 ribu hektare/tahun di tahun 2016. Fakta-fakta deforestasi menggugat keberpihakan Pemerintah Indonesia kepada masyarakat yang tinggal di dalam dan di sekitar hutan. Termasuk merealisasikan keseriusan Pemerintah Indonesia dalam mengurangi emisi, menjaga lingkungan hidup, mencegah bencana, dan melestarikan sumber daya alam. Fakta menunjukkan bahwa 50% dari seluruh daratan di Sumatera Utara, Kalimantan Timur, dan Maluku Utara telah dikuasai oleh pemegang izin konsesi. Hanya 4% dari wilayah daratan yang penguasaan dan pemanfaatannya berada di tangan masyarakat dalam berbagai bentuk program perhutanan sosial dan hutan adat. Fakta menunjukkan juga bahwa degradasi hutan dan deforestasi di provinsi-provinsi ini telah menyebabkan bencana lingkungan: banjir, longsor, kekeringan dan hilangnya habitat satwa dilindungi.
ASEG Webinar Title: Multi-parameter FWI imaging: high-resolution imaging directly from raw field data Presenter: Tom Rayment, Chief Geophysicist, DUG Technology Date: Tuesday 10th May 2022 Abstract: Traditional seismic processing workflows can be extremely time-consuming since subsequent stages are only begun after extensive testing and QC of the current process. This linear approach takes the raw field data and passes it through a plethora of conditioning tools (such as designature, deghosting, demultiple and regularisation) to transform the data into a form that can be imaged by legacy migration algorithms, such as Kirchhoff 3D preSDM. Full waveform inversion (FWI) imaging is a multi-scattering least-squares approach uses the raw field data to estimate many subsurface parameters, including reflectivity, simultaneously ahead of a conventional processing workflow. Since it is using the primaries, multiples and ghosts during imaging, the result is a set of higher resolution subsurface models but in a fraction of the time of a conventional processing workflow due to the fact that little to no pre-processing is required. In this presentation we demonstrate an 85 Hz comparison between a conventional processing workflow and a novel FWI imaging technique that utilises an augmented wave equation and an advanced optimisation scheme. The FWI imaging approach is simultaneously inverting for velocity and an intercept-reflectivity vector which is fit for structural and amplitude analysis.
Provided to YouTube by ONErpm FWI · Seyi Shay · Deborah Oluwaseyi Joshua · David Olakot · Guiltybeatz · Emmanuel Osoba Big Girl ℗ Stargurl Ltd., Jones Worldwide, with exclusive license to ONErpm Released on: 2021-12-10 Producer: Guiltybeatz Auto-generated by YouTube.
Our Chief Geophysicist Tom Rayment showcases the capabilities of DUG Wave—our revolutionary full waveform inversion imaging software—followed by a Q&A session with Managing Director Dr Matthew Lamont.
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Full waveform inversion (FWI) is a high-resolution seismic imaging technique that is based on using the entire content of seismic traces for extracting physical parameters of the medium sampled by seismic waves. Professor Mrinal Sen, Department of Geological Sciences, Jackson School of Geosciences Associate Director, Institute for Geophysics, Jackson School of Geosciences John A. and Katherine G. Jackson Chair in Applied Seismology Morgan J. Davis Centennial Chair in Petroleum Geology More on Prof. Mrinal Sen : 🤍
If fruit could talk, what would they say? These fruit have a lot to discuss as the orange decides being a Christian means showing off his knowledge and wisdom. Si fwi ka pale, ki sa yo ap di? Fwi sa a genyen ampil pou di apre zoranj decide pou toune yon pi bon Kretyen pa montre tout vese e adorasyon li kone.
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ASEG Webinar Branch hosting the event: WA Title: Probabilistic Seismic Full Waveform Inversion (FWI) Presenter: Anandaroop Ray Date: Thursday 11th June, 2:00pm (AEST) Abstract: Probabilistic Seismic Full Waveform Inversion (FWI) Limited illumination, insufficient offset, noisy data and poor starting models can pose challenges for seismic full waveform inversion (FWI). Appropriately formulated Bayesian approaches can mitigate these problems by appealing to parsimony, i.e., low model dimension, and through rigorous quantification of prior knowledge. Given the flexibility of the Bayesian framework, the theory can include the inference of nuisance parameters such as the source wavelet and data noise. Given the tandem developments in statistical inference and HPC, sampling based approaches to FWI are able to provide a surprising amount of subsurface information. While the non-linearity of wave physics is indeed a significant obstacle for inversion algorithms, it is also the reason why inferences, should we reach the appropriate local minima (or posterior probability maxima), are so much more informative than for diffusive or potential field geophysics. Through a combination of synthetic and real data examples, this talk will attempt to encourage further research in this arena. Bio: Anandaroop Ray (“Anand”) started his career as a non-seismic geophysicist with Shell Exploration and Production in 2007. In 2010 he joined the PhD programme in marine electromagnetics at the Scripps Institution of Oceanography in San Diego, California. In 2014 he completed his thesis focusing on uncertainty estimation in electromagnetic inversion for marine hydrocarbon exploration. From 2012-19, he worked for Chevron R&D on various problems – controlled source electromagnetics (CSEM), seismic full waveform inversion (FWI), reservoir properties from seismic (RPFS), airborne electromagnetics (AEM), statistical hydrocarbon exploration lookback analyses, and the role of machine learning in geophysics. The question most asked through his work is “how credibly can we interpret our inversion model(s),” the answering of which often requires the use of high performance computing (HPC) techniques. He currently co-advises a PhD student at Columbia University on Bayesian geophysical inversion, and has been active in convening and organizing the Uncertainty in Geophysical Inversion session at the American Geophysical Union’s Fall Meeting. In March 2019 he joined the Minerals, Energy and Groundwater Division at Geoscience Australia, where he continues to work on inverse uncertainty, model representation and geostatistics.
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An eLearning video for Content Managers to learn the basics of template creation. This video shows the creation of a template with 3 regions. This template will be relied upon in further videos and should be created and saved for future use.
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![Fwi lwi Agwi Fwi - Kiranjit Basumatary [Official Music Video 2019 ]](https://i.ytimg.com/vi/J_kxCLm-ScU/mqdefault.jpg "Fwi lwi Agwi Fwi - Kiranjit Basumatary [Official Music Video 2019 ]")
