Institute of Geophysics, University of TehranJournal of the Earth and Space Physics2538-371X43120170421Estimation of depth, location and structure index of magnetic anomalies by enhanced local wavenumber methodEstimation of depth, location and structure index of magnetic anomalies by enhanced local wavenumber method1151315890910.22059/jesphys.2017.58909FARaminGhasemianniaBehroozOskooiInstitute of Geophysics, Associate Professor0000-0003-3065-194XJournal Article20160223A reliable analysis of magnetic data is the correct estimation of the causative sources to plan for drilling to achieve the targets. This paper presents enhanced local wave number (ELW) method for interpretation of the magnetic data. ELW method has been proposed during the previous decades and is based on analytic signal to estimate the location and depth of the anomalies without having any knowledge about the geometry and magnetic susceptibility of the source. Final equation in this technique, is based on the depth and position and is independent of the structural index. The solution of normal this equation is obtained by assigning ELW kx and kz (the local wave number with respect to x and z) for different values of x and heights of continuation, z within a window centred with the peak of the analytic signal amplitude. A problem of over determined unknown parameters can be solved through a standard technique, using the least squares approach, therefore, the Golub algorithm is used to solve a set of linear equations. The ELW technique requires computation of horizontal and vertical derivatives of the first and second orders. Due to this characteristic, any high frequency noise present in the data gets substantially enhanced, masking the response from a target. To restrict the high frequency response, a window function is designed on the basis of the maximum frequency computed from Agrawal and Lal (1972). After finding these quantities the method can approximate the structure index. Although, an appropriate Matlab code for the method is introduced and tested on two dimensional synthetic data before and after adding noises. There is a peak in the curves of analytic signal and kx of ELW and also a turning point in the curve of kz of ELW witch shows the position of anomaly. Existence of these features shows that final responses of ELW method are correct. Synthetic data produced from a dyke like body with dip, magnetization, declination, inclination, depth and thickness are 45º, 1( ), 90º, 64º, 10m and 15m respectively. The ELW method has had reasonable responses for noises with different amplitudes up to 20nT and for noises with amplitude more than 20nT, ELW method looses its efficiency. Then, the method is tested by applying on the real data of Golbelaghi area in Zanjan, and ok compared with the results obtained from Model vision software. To do this a 525m profile is used. At the end, the depth and structure index are obtained about 4m and 0.8, respectively, using ELW method and the depth is estimated about 4.4m using model vision software. It is worthy to note that the depth of anomaly has been reported 4.5m by drilling. The parameters obtained from the introduced method for the anomalies show that the enhanced local wavenumber method and its introduced Matlab code can be a powerful tool in the studies of local anomalies. Because this method is automatic and quick, it can be used for large data sets like vast area or airborne data. This method is used on airborne data of Damghan region in another paper.A reliable analysis of magnetic data is the correct estimation of the causative sources to plan for drilling to achieve the targets. This paper presents enhanced local wave number (ELW) method for interpretation of the magnetic data. ELW method has been proposed during the previous decades and is based on analytic signal to estimate the location and depth of the anomalies without having any knowledge about the geometry and magnetic susceptibility of the source. Final equation in this technique, is based on the depth and position and is independent of the structural index. The solution of normal this equation is obtained by assigning ELW kx and kz (the local wave number with respect to x and z) for different values of x and heights of continuation, z within a window centred with the peak of the analytic signal amplitude. A problem of over determined unknown parameters can be solved through a standard technique, using the least squares approach, therefore, the Golub algorithm is used to solve a set of linear equations. The ELW technique requires computation of horizontal and vertical derivatives of the first and second orders. Due to this characteristic, any high frequency noise present in the data gets substantially enhanced, masking the response from a target. To restrict the high frequency response, a window function is designed on the basis of the maximum frequency computed from Agrawal and Lal (1972). After finding these quantities the method can approximate the structure index. Although, an appropriate Matlab code for the method is introduced and tested on two dimensional synthetic data before and after adding noises. There is a peak in the curves of analytic signal and kx of ELW and also a turning point in the curve of kz of ELW witch shows the position of anomaly. Existence of these features shows that final responses of ELW method are correct. Synthetic data produced from a dyke like body with dip, magnetization, declination, inclination, depth and thickness are 45º, 1( ), 90º, 64º, 10m and 15m respectively. The ELW method has had reasonable responses for noises with different amplitudes up to 20nT and for noises with amplitude more than 20nT, ELW method looses its efficiency. Then, the method is tested by applying on the real data of Golbelaghi area in Zanjan, and ok compared with the results obtained from Model vision software. To do this a 525m profile is used. At the end, the depth and structure index are obtained about 4m and 0.8, respectively, using ELW method and the depth is estimated about 4.4m using model vision software. It is worthy to note that the depth of anomaly has been reported 4.5m by drilling. The parameters obtained from the introduced method for the anomalies show that the enhanced local wavenumber method and its introduced Matlab code can be a powerful tool in the studies of local anomalies. Because this method is automatic and quick, it can be used for large data sets like vast area or airborne data. This method is used on airborne data of Damghan region in another paper.https://jesphys.ut.ac.ir/article_58909_83562631be3b5219af65dbac74349fd6.pdf