next up previous print clean
Next: Example Up: Theory of wave-equation MVA Previous: Gradient

Linearization

Minimizing the objective function J in Equation (19) involves solving a non-linear least-squares problem using the gradient given by Equation (25).

Alternatively, we can linearize the wavefield $\u$ with respect to a reference wavefield $\v$
\begin{displaymath}
\u = \v + \delta \u= \v + {\bf G}\delta s\end{displaymath} (30)
and optimize  
 \begin{displaymath}
J\left(s\right)
= \frac{1}{2} \left\vert{\bf I}\left(\AA \v - {\bf B}\mathcal T+ \AA {\bf G}\delta s\right)\right\vert^2,\end{displaymath} (31)
which is a linear least-squares problem.

Equation (31) can also be represented by fitting goals using the usual SEP terminology as:
\begin{displaymath}
- {\bf I}\left(\AA \v - {\bf B}\mathcal T\right)\approx {\bf I}\AA {\bf G}\delta s,\end{displaymath} (32)
which takes special forms depending on our choice of the operators $\AA$ and ${\bf B}$:

WEMVA by TIF WEMVA by DSO
$ - {\bf I}\left(\v - \mathcal T\right)\approx {\bf I}{\bf G}\delta s$ $ - {\bf I}\left({\bf D}\v \right)\approx {\bf I}{\bf D}{\bf G}\delta s$

next up previous print clean
Next: Example Up: Theory of wave-equation MVA Previous: Gradient
Stanford Exploration Project
11/11/2002