H.I.A. Hammad
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22 records found
1
Operator-Based Modeling and Inversion
An Operator Approach to the Forward and Inverse Scattering Problems
The kinematical aspects of wave propagation are often analysed using slowness curves, which are well-known not only for isotropic media but also for anisotropic ones. The dynamical aspects are often analysed using reflection coefficient curves which are also well-known for both isotopic and anisotropic media. However, those curves are known for either fully or laterally homogenous rather than heterogeneous media. We generate and analyse those curves in a heterogeneous medium and find that the velocity-normalised slowness curves or cosine-sine curves deviate from the classical circular shape in the homogeneous situation. The deviation is dependent on frequency and hence those curves are dispersive, unlike their counterparts for homogenous media. The reflection coefficient curves also exhibit such deviation from the classical situation involving two homogeneous half spaces. Such deviation in reflection coefficient curves would have an impact on AVO/AVA analysis.
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We extend in this paper the full wave-field modeling method to the elastodynamic situation. While, the acoustic case encompasses directional decomposition - where up-going and downgoing wavefields are modeled in addition to modal decomposition, through which heterogeneity is properly handled - the elastodynamic case encompasses one additional type of decomposition; the one related to polarisations, where the wavefield is separated into its constituent polarisations: quasi-P, quasi-SV, and quasi-SH waves. All three types of decomposition are present in the equations given in this paper. Although we begin with the most general form of equations for anisotropic inhomogeneous media, we reduce those equations to the isotropic case, and we consider only P-SV waves for simplicity. We implement only the squared wavenumber operator, whose implementation closely resembles that of the acoustic case.
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Generalized Full Wavefield Modeling is a directional modeling method, which simulates wavefields such as upgoing and downgoing wavefields. The most straightforward implementation of such a method is to employ the Neumann's iterative method, which is, nonetheless, well-known not to be necessarily convergent for all situations. Thus, we use three other methods that represent a generalization of the Neumann's solution; one is preconditioned stationary overrelaxation, and the other two are preconditioned conjugate gradient and a truncated Krylov method, the so-called GMRes. We compare the convergence of all those methods, as well as, stationary and successive overrelaxation methods without preconditioning. We find that such truncated Krylov method, i.e., GMRes, is overall faster to converge and requires no preconditioning to assure convergence. We show two examples, one using a velocity model linearly increasing with depth and one using a complex salt model adapted from the SEG SEAM model. In the first model, GFWMod provides the upgoing and downing diving waves including the horizontally propagating constituents, while in the second model, it provides the evolution of the scattering process with different iterations, providing insight into the actual scattering process.
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which is, nonetheless, well-known not to be necessarily convergent for all situations. Thus, we use two methods that represent a generalization of the Neumann's solution; one is stationary overrelaxation, and the other is
successive overrelaxation. Both methods attempt to scale the wavefield residual such that it does not grow with increasing number of iterations. One method, stationary overrelaxation, uses a constant scale factor while the other, successive overrelaxation, varies the scale factor with iterations. A numerical example shows clearly that successive overrelaxation yields a stable solution, unlike the other two methods (Neumann's and stationary overrelaxation), since it forces the residual to be reducing in each iteration. ...
which is, nonetheless, well-known not to be necessarily convergent for all situations. Thus, we use two methods that represent a generalization of the Neumann's solution; one is stationary overrelaxation, and the other is
successive overrelaxation. Both methods attempt to scale the wavefield residual such that it does not grow with increasing number of iterations. One method, stationary overrelaxation, uses a constant scale factor while the other, successive overrelaxation, varies the scale factor with iterations. A numerical example shows clearly that successive overrelaxation yields a stable solution, unlike the other two methods (Neumann's and stationary overrelaxation), since it forces the residual to be reducing in each iteration.