... precision. By applying our strategy to a 3D synthetic dataset, we show that the size of kernel matrices used in the Marchenko redatuming and Multi-Dimensional Deconvolution equations can be reduced by a factor of 34 and 6, respectively. We also introduce a TLR Matrix-Vector Multiplication (TLR-MVM...

... migration nonlinear ls-rtm applied geoscience kernel reservoir characterization fwi imaging wavefield multi-parameter fwi reflectivity extended abstract american association chemingui modeling Nonlinear LS-RTM based on the seismic scale separation and full wavefield multi-parameter FWI...

... Using the time-shift fields from dynamic warping can potentially increase the resolution of the velocity tomography in reflection-based full waveform inversion (RFWI). However, procedures for pre-processing of the time-shifts, demigration of images and post-processing of RFWI kernels must...

... on seismic responses and illumination field. In the second part of this study, using velocity inversion kernels, we demonstrate that the elastic properties must be considered when interpreting near surface seismic features. upstream oil & gas seismic response inversion kernel illumination field...

... to obtain due to the errors of acquisition, processing, and the migration velocity model. We propose a kernel prediction neural network (KPN) to flatten the events, correct the depth of the improperly migrated events, and remove the noise and unfocused artifacts in CIGs, and further yield an optimally...

... The reflection waveform inversion (RWI) using the tomographic term of the sensitivity kernel could be an alternative to full waveform inversion (FWI), especially in the deep target area where diving wave is not available. In RWI, the reflection waveform residuals are minimized to invert...

... In this paper, we derived the explicit formulas for the sensitivity kernels for elastic VTI media in terms of practical inversion parameters. Analytical solutions are given for homogeneous isotropic elastic media and the properties of the kernels are discussed. We present an efficient approach...

... In this paper, we discuss the properties of the waveform impedance sensitivity kernel for elastic reverse time migration. A connection is made between the elastic energy norm imaging condition and the impedance sensitivity kernel. It is shown analytically that the imaging condition using...

... Full Wave Inversion (FWI) and Least-Square Reverse Time Migration (LS-RTM) workflows are based on wave propagation simulations. Domain splitting techniques are often used for parallelism. Implementations of finite difference kernels inside each domain and its overlapping with the inter domain...

... skylake node reid atcheson exploration geophysicist 10 numerical algorithm group upstream oil & gas performance comparison optimization seg international exposition kernel reservoir characterization seismic application nec corporation summary application problem size nec...

... these measurements are not available in many data sets. In this paper, we develop a robust support vector machine (SVM) machine learning approach for identifying high TOC formations. A support vector machine is a kernel based classification tool capable of mapping data to a higher dimension and finding an optimal...

... gradient separation kernel waveform inversion frequency rfwi propagative wavenumber reservoir characterization parameterization wavenumber upstream oil & gas central frequency wavelength fresnel zone velocity gradient tomography inversion wavefield iso-angle curve Alkhalifah...

... ABSTRACT Finite frequency model inversion offers higher accuracy than ray-based inversion. The computation of adjoint force is the key to the computation of inversion kernels. Starting from the definition of inversion kernels for the acoustic wave equation, we derive the explicit formula...

... the computation of the Fréchet kernels with respect to both velocity and attenuation based on this wave equation. These kernels will play a fundamental role in the viscoacoustic multiparameter waveform inversion. Presentation Date: Wednesday, September 18, 2019 Session Start Time: 1:50 PM Presentation Time: 2...

... to automatically detect and identify a high percentage of anticlines structures on seismic data. Presentation Date: Wednesday, September 18, 2019 Session Start Time: 1:50 PM Presentation Start Time: 3:05 PM Location: 301B Presentation Type: Oral upstream oil & gas neural network kernel...

...: Poster seg international exposition frequency fwi velocity anomaly kernel broadband seismic velocity model reservoir characterization upstream oil & gas annual international meeting inversion nurrul ismail residual error incised shallow carbonate platform carbonate platform...

...-acoustic model building flow upstream oil & gas seg international exposition model building sequence amplitude fidelity paleocene channel system annual meeting dataset kernel sequence Liu , Z. , S. Brown , A. A. Valenciano , and N. Chemingui , 2016...

... the reflector and enhance the low-wavenumber information in the RWI gradient. Presentation Date: Tuesday, September 17, 2019 Session Start Time: 1:50 PM Presentation Time: 1:50 PM Location: Poster Station 8 Presentation Type: Poster upstream oil & gas kernel wavefield rwi alkhalifah...

... traveltime sensitivity kernel, which is valid for arbitrary velocity perturbation as long as the scatter-angles are small. Then, we solve the associated finite-frequency tomography problem with the Gauss-Newton algorithm. To obtain the Gauss–Newton descent direction, we present a matrix-free Hessian-vector...

... source kernel misfit function rayleigh wave kernel source strength model source strength Bakulin , A. , and R. Calvert , 2006 , The virtual source method: Theory and case study : Geophysics , 71 , no . 4 , SI139 – SI150 , 10.1190/1.2216190 . Dahlen , F...