A new approach for electromagnetic modeling of three-dimensional (3-D) earth conductivity structures using integral equations is introduced. A conductivity structure is divided into many substructures and the integral equation governing the scattering currents within a substructure is solved by a direct matrix inversion. The influence of all other substructures are treated as external excitations and the solution for the whole structure is then found iteratively. This is mathematically equivalent to partitioning the scattering matrix into many block submatrices and solving the whole system by a block iterative method. This method reduces computer memory requirements since only one submatrix at a time needs to be stored. The diagonal submatrices that require direct inversion are defined by local scatterers only and thus are generally better conditioned than the matrix for the whole structure. The block iterative solution requires much less computation time than direct matrix inversion or conventional point iterative methods as the convergence depends on the number of the submatrices, not on the total number of unknowns in the solution. As the submatrices are independent of each other, this method is suitable for parallel processing.

The anisotropy of electrical conductivity in earth formations may be caused by crystal anisotropies of minerals, as well as by minilayers which occur frequently in sedimentary environments. The effects of anisotropy on the propagation of electromagnetic (EM) fields have been studied by many geophysicists. For instance, Kong (1972) and Wait (1981) solved the EM propagation problem for vertically anisotropic layered earths; O’Brien and Morrison (1967), for a horizontally anisotropic multilayer half‐space; Chetayev (1960), as well as Reddy and Rankin (1971), for media of dipping anisotropies; and Al’tgauzen (1969), for more complicated anisotropic media with a tensor dielectric constant of five components.

Using the staggered grid full domain 3D modeling schemes of various accuracies have been developed. This study focuses on the second order finite difference method with the 13-point rule for meshes extending into the air. Tests with Krylov space iterative solvers indicate that the restarted Bi-CG Stablised method offers the best convergence for our problems. Because the air and the conductive earth have distinctive physical properties which greatly broaden the spectra of the whole matrix system, the whole mesh with both domains in one system either converges very slowly or fails to converge completely. However, the matrix systems for each domain have much smaller condition numbers. To overcome instability caused by the inclusion of the air in the mesh a domain decomposition method are experimented. Tests show that the adaptive iteration amongst the subdomains converges exponentially, which implies that large models can be solved by using the domain decomposition method.

An electromagnetic scattering algorithm for large conductivity structures in stratified media has been developed and is based on the method of system iteration and spatial symmetry reduction using volume electric integral equations. The method of system iteration divides a structure into many substructures and solves the resulting matrix equation using a block iterative method. The block submatrices usually need to be stored on disk in order to save computer core memory. However, this requires a large disk for large structures. If the body is discretized into equal‐size cells it is possible to use the spatial symmetry relations of the Green's functions to regenerate the scattering impedance matrix in each iteration, thus avoiding expensive disk storage. Numerical tests show that the system iteration converges much faster than the conventional point‐wise Gauss‐Seidel iterative method. The numbers of cells do not significantly affect the rate of convergency. Thus the algorithm effectively reduces the solution of the scattering problem to an order of O(N2), instead of O(N3) as with direct solvers.

Modeling large three‐dimensional (3-D) earth conductivity structures continues to pose challenges. Although the theories of electromagnetic modeling are well understood, the basic computational problems are practical, involving the quadratically growing requirements on computer storage and cubically growing computation time with the number of cells required to discretize the modeling body.