Depth Estimation of Ground Magnetic Anomalies using Standard Euler Deconvolutionin the Reshm area, Semnan

Depth estimation of the top of the bedrock in the sedimentary basins is the main goal in geomagnetic explorations. The depth estimation of this kind of anomalies can be done using different methods, in the cases where the bedrock is magnetized. In this article, we use the standard Euler deconvolution method and its results to interpret the magnetic data from the Reshm region in Semnan province of Iran. The estimated depths of the top of major anomalies in the area are resembled as 100 m and 135 m.
In the potential field explorations, both of the depth estimation and the horizontal position detection of the source of anomalies and as a result, the imagination of the source of anomaly is the main purpose of exploration. Some methods can lead us to these purposes such as Euler deconvolution, Peters, Werner deconvolution, Analytical Signal, AN-EUL methods etc.
Some methods such as the Analytical Signal can just show the horizontal positions of the anomalies. And some such as the Peters method can show just the depth of anomalies. The standard Euler deconvolution method can provide the estimated depths of anomalies and the horizontal region covering the source of the anomalies.
In this paper we used Geosoft Oasis Montaj 6.4.2 software and also a Matlab code written by Durrheim and Cooper.
The standard Euler method is based on the Euler equation, and using this method in the depth estimation of magnetic anomalies inserts the geology of the region into the calculations. A drawback of the Euler deconvolution is the scattering of the solutions estimated at different data window positions.
We derive the analytical estimators for the horizontal and vertical source positions in 3D Euler deconvolution as a function of the x-, y-, and z-derivatives of the magnetic anomaly within a data window. From these expressions we show that, in the case of noise-corrupted data, the x-, y-, and z-coordinate estimates computed at the anomaly borders are biased toward the respective horizontal coordinate of the data window center regardless of the true or presumed structural indices and regardless of the magnetization inclination and declination.
On the other hand, in the central part of the anomaly, the x- and y-coordinate estimates are very close to the respective source horizontal coordinates regardless of the true or presumed structural indices and regardless of the magnetization inclination and declination. This contrasting behavior of the horizontal coordinate estimates may be used to automatically delineate the region associated with the best solutions. Applying the Euler deconvolution operator inside this region would decrease the dispersion of all position estimates, improving source location precision.