Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 7 of 7 for “"Cycle skipping"”.
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Investigation of Source Extension Methods, the Discrepancy Algorithm, and Noise Estimation to Overcome Cycle Skipping in Full Waveform Inversion
… at a suboptimal solution, a problem known as cycle-skipping. This dissertation explores several source extension methods to overcome the cycle-skipping problem in FWI for transmitted data. These methods add additional degrees of freedom to the objective function, expanding the solution space …
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Learning Seismic Waves for Imaging the Earth
… waves are essential to mitigate the cycle-skipping problem of full-waveform inversion (FWI), but data below ∼ 3 Hz are missing due to the band-limited characteristic of conventional artificial sources. Here we train convolutional neural networks to computationally extrapolate …
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Accelerating RTL Simulation Through Fine-grained Task Dataflow and Selective Execution
… only the fraction of the design exercised each cycle, skipping ineffectual tasks. ASH hardware provides a novel combination of dataflow and speculative execution, and ASH’s compiler features several novel techniques to automatically leverage this hardware. We evaluate ASH in simulation using …
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Task Scheduling Techniques to Accelerate RTL Simulation
… only the fraction of the design exercised each cycle, skipping ineffectual tasks. Selective execution introduces dynamic data dependences since skipped tasks do not communicate data. ASH employs speculative execution to handle these dependencies. ASH’s hardware provides a novel combination of …
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Deep learning methods for shear log predictions in the Volve field Norwegian North Sea
… poor quality due to poor borehole conditions, or cycle-skipping. This thesis discusses artificial neural networks (ANNs) for shear log predictions using data from the Volve field, in the Norwegian North Sea. In this thesis I use deep neural networks or feedforward neural networks, and I propose …
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Acoustic full-waveform to elastic pre-stack seismic inversion of the Yakutat Terrane, Gulf of Alaska
… scheme. Drawbacks associated with FWI is cycle skipping during the minimization process, which results in converging to the wrong velocity model. Starting with a good initial model that contains the low-frequency information can help mitigate this issue. The starting velocity model input …
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Full-waveform inversion of time-lapse seismic data using physics-based and data-driven techniques
… The multiscale approach is adopted to mitigate cycle-skipping. Synthetic tests show that the proposed methodology can reconstruct localized time-lapse parameter variations with sufficient spatial resolution. The DD strategy produces the most accurate results for clean and repeatable time-lapse …