... that greatly enhances the robustness of ES-FWI. structural geology initial model geophysics application inversion fwi source-focusing function geologist reservoir characterization waveform inversion applied geoscience & energy 10 exploration geophysicist american association first-scale...

... full waveform inversion (JDFWI) for velocity model update, and one way wave equation multiple migration (OWEMM) method were used to generate final imaging. The results provide client with good quality imaging in a relatively large subsurface area. geologist vertical seismic profile migration...

... Acoustic full-waveform inversion is often able to build highquality velocity models for sub-salt imaging using only acoustic wave propagation. This is achieved by adaptively matching acoustic data to the real-world elastic field data. Here we show both acoustic and elastic adaptive waveform...

... Full waveform inversion (FWI) is crucial for reconstructing high-resolution subsurface models, but it is hindered by its computational intensity, especially for real-time applications. Leveraging learned wavefield solutions using a Fourier neural operator (FNO), we introduce a novel physics...

... Full waveform inversion (FWI) has great potential in reconstructing high-resolution subsurface models. However, due to limitations in observation, this inverse problem is highly ill-posed, especially for recovering a 3D velocity model. To solve this problem, regularization is often used, like...

... Majority of full waveform inversion (FWI) implementations are based on local optimization methods. However, due to the high nonlinearity of the forward problem, FWI is challenged with the well-known local minima issue. Traditional FWI methods often require observed data to have low frequency...

... Dynamic Matching Full Waveform Inversion (DM FWI) has been established as a proven toolkit to update velocity models. Mao et al. (2020) demonstrated its success for datasets where long offsets, wide azimuths are available. Yong et al. (2023) showcased reliable and effective updates for offsets...

... Elastic full-waveform inversion (EFWI) promises to account for the Earth’s elastic nature and corresponding reflectivity, which is often disregarded in the commonly used acoustic FWI. However, EFWI usually requires a more sophisticated recording apparatus (beyond the usual single-component data...

... Full-waveform inversion (FWI) has been widely applied to marine datasets with remarkable success. However, there are still significant challenges for FWI applications of land data, due to limited acquisition offsets, shot-dependent source signatures, and complex near-surface conditions etc. Here...

... One fundamental challenge of full-waveform inversion (FWI) is the local minimum issue caused by the cycle skipping between the predicted and observed data. Our proposed Time-Adaptive FWI (TA-FWI) is designed to build the relation between travel time shift and model error in a different and novel...

... and the limitation of low-wavenumber information in full-waveform inversion. It also better captures the sparsity of the velocity model gradient, thereby preserving important underground structural boundaries and details during the inversion process. Additionally, we enhance the stability and accuracy...

... Receiver-based extension strategy introduces additional degrees of freedom to full waveform inversion, in order to improve the fit between the observed and calculated data at early iterations. This helps circumvent the cycle-skipping phenomenon. The additional degrees of freedom are the receiver...

... characterization reflectivity method sedimentary rock rock type tight sandstone thin reservoir geologist inversion seismic record applied geoscience & energy 10 slowness anisotropic rapid reflectivity method exploration geophysicist waveform inversion vti media algorithm american association...

... We apply extended full waveform inversion (FWI) to GOM data to improve subsalt imaging. Extended FWI extends the surface data matching with time shift and utilizes relative matching to mitigate the cycle-skipping and amplitude discrepancy. Both synthetic and field data examples demonstrate...

...). To fully realize the qualities of PINNs in a scenario where multiple (wavefield) solutions are needed, e.g., full waveform inversion (FWI), we introduce latent representation learning to PINNs. To do this, we first append the input (source-receiver coordinate points) with the encoded velocity (latent...

... Full-waveform inversion approaches aim to recover the subsurface model parameters with high resolution and accuracy. However, mainly due to its non-linear nature and high computational cost, the inversion process may result in an estimated model with low resolution and high uncertainty...

... the degree of processing steps the data may have to go through. Current study shows the effect of near offset data and variation of velocity gradient in seismic modeling for shallow subsurface investigation using full waveform inversion. This paper presents three experiments to show the relation between...

... Reflection waveform inversion (RWI) is a well-known technique used to recover deep velocity models by utilizing reflection data. However, RWI is inherently an ill-posed inversion problem and incorporating prior information can help reduce the null space and improve the conditioning...

... Such geophysical fields as reservoir modelling, oil and gas exploration, CO 2 sequestration, require robust subsurface velocity models. The state-of-the art approach to velocity inversion is the full waveform inversion (FWI) method. While FWI can lead to high-resolution velocity inversion...

... must be taken into account. The elastic characteristics of rock samples may be precisely characterized using ultrasonic tomography technology, which can also be utilized to find interior flaws or heterogeneity. Full waveform inversion, nevertheless, has lately attracted more attention. We can build...