Mapping thin resistors and hydrocarbons with marine EM methods, Part II — Modeling and analysis in 3D

Geophysics ◽  
2006 ◽  
Vol 71 (6) ◽  
pp. G321-G332 ◽  
Author(s):  
Chester J. Weiss ◽  
Steven Constable

The electromagnetic fields surrounding a thin, subseabed resistive disk in response to a deep-towed, time-harmonic electric dipole antenna are investigated using a newly developed 3D Cartesian, staggered-grid modeling algorithm. We demonstrate that finite-difference and finite-volume methods for solving the governing curl-curl equation yield identical, complex-symmetric coefficient matrices for the resulting [Formula: see text] linear system of equations. However, the finite-volume approach has an advantage in that it naturally admits quadrature integration methods for accurate representation of highly compact or exponentially varying source terms constituting the right side of the resulting linear system of equations. This linear system is solved using a coupled two-term recurrence, quasi-minimal residual algorithm that doesnot require explicit storage of the coefficient matrix, thus reducing storage costs from [Formula: see text] to [Formula: see text] complex, double-precision words with no decrease in computational performance. The disk model serves as a generalized representation of any number of resistive targets in the marine environment, including basaltic sills, carbonates, and stratigraphic hydrocarbon traps. We show that spatial variations in electromagnetic phase computed over the target are sensitive to the disk boundaries and depth, thus providing a useful complement to the usual amplitude-versus-offset analysis. Furthermore, we estimate through the calculation of Fréchet sensitivity kernels those regions of the 3D model which have the greatest effect on seafloor electric fields for a given source/receiver configuration. The results show that conductivity variations within the resistive disk have a stronger influence on the observed signal than do variations in the surrounding sediment conductivity at depth.

Author(s):  
J. Vasundhara Devi ◽  
Sadashiv G. Deo ◽  
Ramakrishna Khandeparkar

2020 ◽  
Vol 13 (1) ◽  
pp. 1-15
Author(s):  
Tesfaye Kebede Enyew ◽  
Gurju Awgichew ◽  
Eshetu Haile ◽  
Gashaye Dessalew Abie

Although large and sparse linear systems can be solved using iterative methods, its number of iterations is relatively large. In this case, we need to modify the existing methods in order to get approximate solutions in a small number of iterations. In this paper, the modified method called second-refinement of Gauss-Seidel method for solving linear system of equations is proposed. The main aim of this study was to minimize the number of iterations, spectral radius and to increase rate of convergence. The method can also be used to solve differential equations where the problem is transformed to system of linear equations with coefficient matrices that are strictly diagonally dominant matrices, symmetric positive definite matrices or M-matrices by using finite difference method. As we have seen in theorem 1and we assured that, if A is strictly diagonally dominant matrix, then the modified method converges to the exact solution. Similarly, in theorem 2 and 3 we proved that, if the coefficient matrices are symmetric positive definite or M-matrices, then the modified method converges. And moreover in theorem 4 we observed that, the convergence of second-refinement of Gauss-Seidel method is faster than Gauss-Seidel and refinement of Gauss-Seidel methods. As indicated in the examples, we demonstrated the efficiency of second-refinement of Gauss-Seidel method better than Gauss-Seidel and refinement of Gauss-Seidel methods.


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