WebAug 5, 2024 · Full-waveform inversion (FWI) is a challenging data-fitting procedure based on full-wavefield modeling to extract quantitative information from seismograms. High … WebABSTRACT Seismic full-waveform inversion (FWI) is potentially a powerful method for obtaining high-resolution subsurface images, but the results are often distorted by nonlinear effects and parameter trade-offs. Such distortions can be particularly severe in the case of multiparameter FWI, such as elastic FWI, in which inversion is performed simultaneously …
An overview of full-waveform inversion in exploration …
WebDec 16, 2024 · Traditional full-waveform inversion (FWI) methods only render a “best-fit” model that cannot account for uncertainties of the ill-posed inverse problem. Additionally, local optimization-based FWI methods cannot always converge to a geologically meaningful solution unless the inversion starts with an accurate background model. WebJan 4, 2024 · Full-waveform inversion (FWI) can obtain the highest resolution in traditional velocity inversion methods, but it heavily depends on initial models and is … goodlandpottery.com
KIT - Research - Applied Geophysics - Software
WebExperienced Data Scientist and Research Geophysicist with a demonstrated history of working in the oil & energy industry. Skilled in deep learning, … WebFirst-arrival waveform inversion using low-frequency regenerated data. K Xu*, C Macesanu. SEG Technical Program Expanded Abstracts 2016, 5665-5669. , 2016. 2. 2016. 3D scalar-wave absorbing boundary conditions with optimal coefficients in the frequency-space domain. K Xu, GA McMechan. Geophysics 77 (3), T83-T96. WebJan 22, 2024 · I demonstrate that the conventional seismic full-waveform inversion algorithm can be constructed as a recurrent neural network and so implemented using deep learning software such as TensorFlow. Applying another deep learning concept, the Adam optimizer with minibatches of data, produces quicker convergence toward the true wave speed … goodland pool services