... & gas conventional fwi fwi adaptive reflection waveform inversion refracted arrival Adaptive reflection waveform inversion: faster, tighter, deeper, smarter Mike Warner, Tenice Nangoo, Adrian Umpleby, Nikhil Shah, S-Cube; Dan Kahn, Mik Isernia, AWS. Summary Here, we demonstrate a third approach...

...: 11:00 AM Location: 351D Presentation Type: Oral reservoir characterization frequency selection relaxation optimization problem objective function waveform inversion artificial intelligence constraint conventional fwi wri upstream oil & gas initial model wavefield inversion...

... inversion (FWI). It mitigates the presence of local minima within the conventional FWI objective function by creating improved descent-paths towards the optimal solution. Its consistent and concise mathematical formulation paired with an automatized implementation makes it simple to apply and thus more...

... from poor initial models without stagnation at suboptimal models encountered by conventional FWI. Presentation Date: Monday, October 12, 2020 Session Start Time: 1:50 PM Presentation Time: 3:55 PM Location: Poster Station 3 Presentation Type: Poster reservoir characterization frequency...

... with intermediate data updates the background velocity model in the correct direction. Thus, it produces a background velocity model accurate enough for carrying out conventional FWI to rebuild the intermediate- and short-wavelength components of the velocity model. Our numerical examples using synthetic data...

... & gas diffusion equation marmousi model anomaly background velocity rwi columnlike anomaly information full-waveform inversion conventional fwi waveform inversion Bunks , C. , F. Saleck , S. Zaleski , and G . Chavent , 1995 , Multiscale seismic waveform...

.... To mitigate the strong artifact from the tomographic kernel from RFWI while satisfying the requirement for Born assumptions, we design a preconditioned optimization scheme which improves the convergence rate with less artifacts and provides a better initial model for applying conventional FWI in the following...

... ABSTRACT Due to high nonlinearlity in terms of optimization, the conventional FWI such as weighted L2, shifted Laplace domain FWI and FWI using deconvolution objective function, has been failed to achieve successful FWI. The nonlineality in FWI is mostly caused by the absence of low frequency...

... representation coefficients instead of being updated directly. Synthetic tests show that the proposed DL-FWI is more robust than the conventional FWI against the noise while revealing the detailed subsurface structures. Presentation Date: Monday, September 16, 2019 Session Start Time: 1:50 PM Presentation...

... modifications in DWFWI compared to conventional FWI: (1) Waveform gradient and misfit function are weighted by data covariance matrix to suppress artifacts from data with low signal-to-noise ratio and to determine stopping criteria for the inversion; (2) FWI penalty function optimization using adaptive moment...

... waveform inversion (CFIWI) by emphasizing the travel-time difference between intensities. Applications to the Marmousi model and Chevron blind test model demonstrate that the CFIWI converges to an acceptable initial model for conventional FWI, displaying high efficiency even with inaccurate source wavelets...

...-frequency data required by conventional FWI. Presentation Date: Wednesday, September 18, 2019 Session Start Time: 8:30 AM Presentation Time: 10:10 AM Location: 225B Presentation Type: Oral upstream oil & gas machine learning constraint conventional fwi tsvankin algorithm reservoir...

... full-waveform inversion maximum amplitude conventional fwi inversion result fwi artificial intelligence inversion ABSTRACT Full-waveform inversion is a promising tool to produce accurate and high-resolution subsurface elastic models. Accurate estimation of the source wavelet is required...

... conventional fwi seg international exposition equation perturbation vector data formulation tradeoff inversion artificial intelligence Akrami , S. M. , P. Zheglova , and A. Malcolm , 2017 , An algorithm for vector data full-waveform inversion : 87th Annual International...

... the vicinity of the current model estimate. Through numerical analyses, we find that the gradients corresponding to slightly perturbed velocity models can be approximated by space-shifting the gradient obtained from current velocity model. The computational cost is thus the same as conventional FWI. Numerical...

... inversion perturbation conventional fwi full waveform inversion reservoir characterization fwime workflow seg international exposition fwi objective function inversion Barnier , G. , E. Biondi , and B. Biondi , 2018 , Tomographic full waveform inversion with variable...

... wavefield-separation scheme, rather than using the reflection waveform inversion under the Born-approximation. We validate our new FWI method using synthetic data for the Marmousi model. We demonstrate that that our new method is more robust than conventional FWI, particularly when initial velocity models...

... for conventional FWI, the success in providing reliable updated models heavily relies on the accuracy of the initial models and low frequency contents in the acquired data. To relax the requirements of good initial models and adequate low frequencies, we propose a novel approach to time domain reconstructed full...

... ABSTRACT Wave-equation Traveltime Inversion (WTI) is a good method for building background velocity models, and it can provide a good initial velocity model for full waveform inversion (FWI). But, sometimes, the WTI result is not good enough for conventional FWI, while in order to calculate...

... on reflected seismic wave : 82nd Annual International Meeting, SEG, Expanded Abstracts , 1 – 7 , 10.1190/segam2012-1473.1 . wavefield velocity field full waveform inversion seg seg international exposition sensitivity kernel conventional fwi annual meeting fwi upstream oil & gas...