26 research outputs found
2.5D regularized inversion for the interpretation of residual gravity data by a dipping thin sheet: numerical examples and case studies with an insight on sensitivity and non-uniqueness
Tracing of paleo-shear zones by self-potential data inversion: case studies from the KTB, Rittsteig, and Grossensees graphite-bearing fault planes
A quasi-analytical boundary condition for three-dimensional finite difference electromagnetic modeling
Journal ArticleNumerical modeling of the quasi-static electromagnetic (EM) field in the frequency domain in a three-dimensional (3-D) inhomogeneous medium is a very challenging problem in computational physics. We present a new approach to the finite difference (FD) solution of this problem. The FD discretization of the EM field equation is based on the balance method. To compute the boundary values of the anomalous electric field we solve for, we suggest using the fast and accurate quasi-analytical (QA) approximation, which is a special form of the extended Born approximation. We call this new condition a quasi-analytical boundary condition (QA BC). This approach helps to reduce the size of the modeling domain without losing the accuracy of calculation. As a result, a larger number of grid cells can be used to describe the anomalous conductivity distribution within the modeling domain. The developed numerical technique allows application of a very fine discretization to the area with anomalous conductivity only because there is no need to move the boundaries too far from the inhomogeneous region, as required by the traditional Dirichlet or Neumann conditions for anomalous field with boundary values equal to zero. Therefore this approach increases the efficiency of FD modeling of the EM field in a medium with complex structure. We apply the QA BC and the traditional FD (with large grid and zero BC) methods to complicated models with high resistivity contrast. The numerical modeling demonstrates that the QA BC results in 5 times matrix size reduction and 2-3 times decrease in computational time
A Rapid technique for estimating the depth and width of a two-dimensional plate from self-potential data
Rapid techniques for self-potential (SP) data interpretation are of prime importance in engineering and exploration geophysics. Parameters (e.g. depth, width) estimation of the ore bodies has also been of paramount concern in mineral prospecting. In many cases, it is useful to assume that the SP anomaly is due to an ore body of simple geometric shape and to use the data to determine its parameters. In light of this, we describe a rapid approach to determine the depth and horizontal width of a two-dimensional plate from the SP anomaly. The rationale behind the scheme proposed in this paper is that, unlike the two- (2D) and three-dimensional (3D) SP rigorous source current inversions, it does not demand a priori information about the subsurface resistivity distribution nor high computational resources. We apply the second-order moving average operator on the SP anomaly to remove the unwanted (regional) effect, represented by up to a third-order polynomial, using filters of successive window lengths. By defining a function F at a fixed window length (s) in terms of the filtered anomaly computed at two points symmetrically distributed about the origin point of the causative body, the depth (z) corresponding to each half-width (w) is estimated by solving a nonlinear equation in the form ξ(s, w, z) = 0. The estimated depths are then plotted against their corresponding half-widths on a graph representing a continuous curve for this window length. This procedure is then repeated for each available window length. The de pth and half-width solution of the buried structure is read at the common intersection of these various curves. The improvement of this method over the published first-order moving average technique for SP data is demonstrated on a synthetic data set. It is then verified on noisy synthetic data, complicated structures and successfully applied to three field examples for mineral exploration and we have found that the estimated depth is in good agreement with the known value reported in the literature.10 page(s
A fast imaging method for the interpretation of self-potential data with application to geothermal systems and mineral investigation
Abstract We describe a rapid imaging approach for the interpretation of self-potential data collected along profile by some geometrically simple model of cylinders and spheres. The approach calculates the correlation coefficient between the analytic signal (AS) of the observed self-potential measurements and the AS of the self-potential signature of the idealized model. The depth, electric dipole moment, polarization angle, and center are the inverse parameters we aim to extract from the imaging approach for the interpretative model, and they pertain to the highest value of the correlation coefficient. The approach is demonstrated on noise-free numerical experiments, and reproduced the true model parameters. The accuracy and stability of the proposed approach are examined on numerical experiments contaminated with realistic noise levels and regional fields prior to the interpretation of real data. Following that, five real field examples from geothermal systems and mineral exploration have been successfully analyzed. The results agree well with the published research