A.R. Arab-Amiri; A. Moradzadeh; D. Rajabi; B. Siemon; N. Fathianpour
Abstract
It is about 30 years that Helicopter electromagnetic (HEM) surveys are being used for rapid mineral and ground water exploration, environmental investigations and also geological mapping in extensive areas. Despite this, one of the most important problems in using obtained data from the surveys is accurate ...
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It is about 30 years that Helicopter electromagnetic (HEM) surveys are being used for rapid mineral and ground water exploration, environmental investigations and also geological mapping in extensive areas. Despite this, one of the most important problems in using obtained data from the surveys is accurate interpretation of the data. Otherwise, there will be no beneficial results while spending high costs. Thus the interpretation of the data is as old as the surveys. Several experts have tried to improve the interpretation of HEM data and they have achieved great successes. Almost the results of all these surveys are presented as resistivity (or conductivity)-depth sections. To reach this target, the first step is to solve the electromagnetic induction integral equation. As solving this integral is not possible using analytical methods, several numerical methods such as Laplace transformation, Hankel transformation and Jacobi-Matrix methods have been suggested for the solution of the integral, and different approaches have been presented with each method by various authorities. One of the most important solution methods is fast Hankel transformation. In this paper, it is attempted to use this method for finally obtaining resistivity-depth sections. For solving the induction equation by this method, we need the kernel function of the integral and weighting coefficients that replace the Bessel function in the integral. For this, first we use the Guptasarma-Singh method. Then results of this method are corrected and evaluated. Then, these results will be analyzed and tested with two synthetic models in addition to presenting the results of inverse modeling. Finally, by adding new parameter named α0 to induction equation, we will clearly see an improvement in the results of inverse modeling. Meanwhile, the problem of singularity that occurs at high frequencies is almost removed.
