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Optimization of the objective function in Equation (19)
requires computation of its gradient with respect to slowness.
The objective function J can be rewritten using the
inner product as:
|  |
(20) |
A perturbation of the function J is related to a perturbation
of the wavefield by the relation:
|  |
(21) |
If we replace
from Equation (11) we obtain:
|  |
(22) |
therefore the gradient of the objective function can be written as
|  |
(23) |
Following the definition of the operator
, we can write
| ![\begin{displaymath}
{\bf G}^* = {\bf S}^* {\bf E}^* \left[\left({\bf 1}- {\bf E}...
...bf E}^* \left[\left({\bf 1}- {\bf E}\right)^{ *} \right]^{-1} .\end{displaymath}](img61.gif) |
(24) |
Finally, the expression for the gradient of the objective function
with respect to slowness becomes
|  |
(25) |
which takes special forms depending on our choice of the
operators
and
:
| WEMVA by TIF |
WEMVA by DSO |
![$ \nabla_sJ= {\bf S}^* {\bf E}^* \left[\left({\bf 1}- {\bf E}\right)^{ *} \right]^{-1}
{\bf I}^* {\bf I}\left(\u - \mathcal T\right)$](img63.gif) |
![$ \nabla_sJ= {\bf S}^* {\bf E}^* \left[\left({\bf 1}- {\bf E}\right)^{ *} \right]^{-1}
{\bf D}^* {\bf I}^* {\bf I}{\bf D}\u $](img64.gif) |
The gradient in Equation (25)
is computed using the adjoint state
method, which can be summarized by the following steps:
- 1.
- Compute by downward continuation the wavefield
|  |
(26) |
- 2.
- Compute by upward continuation the adjoint state wavefield
| ![\begin{displaymath}
\mathcal W= \left[\left({\bf 1}- {\bf E}\right)^{ *} \right]...
...\AA^* {\bf I}^* {\bf I}\left(\AA \u - {\bf B}\mathcal T\right),\end{displaymath}](img66.gif) |
(27) |
i.e. solve the adjoint state system
|  |
(28) |
- 3.
- Compute the gradient
|  |
(29) |
Next: Linearization
Up: Theory of wave-equation MVA
Previous: Objective function
Stanford Exploration Project
11/11/2002