Title :
An enhanced Gauss-Newton inversion algorithm using a dual-optimal grid approach
Author :
Abubakar, Aria ; Habashy, Tarek M. ; Druskin, Vladimir L. ; Knizhnerman, Leonid
Author_Institution :
Schlumberger-Doll Res., Ridgefield, CT, USA
fDate :
6/1/2006 12:00:00 AM
Abstract :
We developed two algorithms for solving the nonlinear electromagnetic inversion problem in the Earth. To achieve a balance between efficiency and robustness, both algorithms employ the Gauss-Newton inversion method. Moreover, to speed up the inversion´s computational time, the so-called optimal grid technique is utilized. The first algorithm uses a forward solver with a very coarse optimal grid to calculate the Jacobian matrix. Hence, in this scheme we employ two different sets of optimal grids. One set is used to compute the data mismatch to be minimized and the other set is used to construct the Jacobian matrix. In the second approach we use a fixed-point iteration process where the inverse kernel is approximated on a coarse optimal grid that does not significantly compromise accuracy. The advantage of these optimal grids is that they considerably reduce the computation time without compromising accuracy. Numerical examples for two-dimensional axially symmetric and three-dimensional anisotropic configurations are used to demonstrate the advantage of using both algorithms over the standard Gauss-Newton inversion method.
Keywords :
Jacobian matrices; electromagnetic waves; finite difference methods; inverse problems; iterative methods; terrestrial electricity; well logging; 2D axially symmetric configuration; 3D anisotropic configuration; Jacobian matrix; computational time; dual optimal grid approach; enhanced Gauss-Newton inversion; fixed point iteration process; forward solver; nonlinear electromagnetic inversion problem; Conductivity; Cost function; Earth; Gaussian processes; Grid computing; Jacobian matrices; Least squares methods; Newton method; Recursive estimation; Robustness; Finite-difference; induction; inversion; multicomponent; optimal grid; optimization; resistivity; three-dimensional (3-D);
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2006.872297