Comparing the results of applying the AN-EUL on magnetic data, reduced to the pole data and pseudo gravity data

Document Type : Research Article

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Abstract

AN-EUL is a new automatic method for the simultaneous approximation of depth, geometry and location of magnetic sources. The principle advantage of this method is its combining both the analytic signal and the Euler Deconvolution methods. It is by substituting the appropriate derivatives of Euler homogeneous equations for the expression of the analytic signal of the potential field in the main equations of this method that the advantage is gained. In this method, the determination of the source location is based on the position of the maximum value of the analytic signal amplitude. For 3D sources, the maximum value of the amplitude of analytic signals (AAS) is not always located directly over the body, and the shape of AAS is dependent on the magnetization direction. Therefore, there are some errors in the determination of location based on the maximum value of AAS for these types of sources. Consequently, the calculation of the depth and structural indices, also have errors when using the maximum value of AAS. By using the reduction to the pole and pseudo gravity transform of the magnetic anomaly, the approximation of the source location and, consequently, the calculation of the depth and structural indices of the source gain high accuracy. In this paper, in order to compare results, the AN-EUL method has been applied to magnetic data, reduced to the pole data and pseudo gravity data due to the magnetic sphere. The results show that the calculations have greater accuracy for reduced to the pole data and pseudo gravity data than for magnetic data. Finally, this method is applied to a series of real magnetic data. By using the reduction to the pole and pseudo gravity filters, the reduced to the pole and pseudo gravity anomalies are calculated. Subsequently, the AN-EUL method is applied to these data, and the results are compared with each other. All of the steps in this paper are performed by using a written code in MATLAB.
 
 

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