Accumulated energy norm for full waveform inversion of marine data

2017 ◽  
Vol 147 ◽  
pp. 91-101 ◽  
Author(s):  
Changsoo Shin ◽  
Wansoo Ha
Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. R307-R320 ◽  
Author(s):  
Ju-Won Oh ◽  
Tariq Alkhalifah

The orthorhombic (ORT) anisotropic description of earth layers can allow the capture of much of the earth’s anisotropic complexity. The inversion for high-resolution azimuthal variation of anisotropy is important for reservoir characterization, among other applications. A high-resolution description of the azimuth of fractures can help us to predict flow preferences. To verify the feasibility of multiparameter full-waveform inversion (FWI) for marine data assuming azimuthally rotated elastic ORT media, we have analyzed the radiation patterns and gradient directions of ORT parameters to the reflection data. First, we express the gradient direction of the ORT parameters considering the azimuthal rotation of the symmetric planes. Then, to support our observations in the gradient direction, the radiation patterns of the partial derivative wavefields from each parameter perturbation are also derived under the rotated elastic ORT assumption. To find an optimal parameterization, we compare three different parameterizations: monoclinic, velocity-based, and hierarchical parameterizations. Then, we suggest an optimal multistage update strategy by analyzing the behavior of the rotation angle as a FWI target. To analyze the trade-off among parameters in different parameterizations, we calculate the gradient direction from a hockey-puck model, in which each parameter is perturbed at the different location on a horizontal layer. The trade-off analysis supports that the hierarchical parameterization provides us with more opportunities to build up subsurface models with less trade-off between parameters and less influence of the azimuthal rotation of ORT anisotropy. The feasibility of the proposed FWI strategy is examined using synthetic marine streamer data from a simple 3D reservoir model with a fractured layer.


Geophysics ◽  
2012 ◽  
Vol 77 (3) ◽  
pp. A13-A17 ◽  
Author(s):  
Xiang Li ◽  
Aleksandr Y. Aravkin ◽  
Tristan van Leeuwen ◽  
Felix J. Herrmann

Wave-equation-based seismic inversion can be formulated as a nonlinear least-squares problem. The demand for higher-resolution models in more geologically complex areas drives the need to develop techniques that exploit the special structure of full-waveform inversion to reduce the computational burden and to regularize the inverse problem. We meet these goals by using ideas from compressive sensing and stochastic optimization to design a novel Gauss-Newton method, where the updates are computed from random subsets of the data via curvelet-domain sparsity promotion. Two different subset sampling strategies are considered: randomized source encoding, and drawing sequential shots firing at random source locations from marine data with missing near and far offsets. In both cases, we obtain excellent inversion results compared to conventional methods at reduced computational costs.


2015 ◽  
Vol 6 (2) ◽  
pp. 5-16 ◽  
Author(s):  
Sergio Alberto Abreo Carrillo ◽  
Ana B. Ramirez ◽  
Oscar Reyes ◽  
David Leonardo Abreo-Carrillo ◽  
Herling González Alvarez

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