A new method of edge detection of magnetized structures using the modulus of full tensor potential field gradient

Edge detection of causative bodies is important in the interpretation of potential field data. There are many methods that can be employed to detect and enhance the edges. In recent years, many filters have been presented based on potential field gradient tensor data. Because of using nine signal components, these methods have a very high accuracy compared to previous proposed methods in this regard. In this paper, normalized horizontal modulus (NHM) method, based on the potential field gradient tensor data, has been proposed. This method makes use of the modulus of potential field gradient tensor to normalize the horizontal modulus of potential field gradient tensor. The minimum value of NHM specifies the edge of magnetized structures. The proposed method with very high degree of precision delineates the edges of anomalies and does not show distraction. This new filter is tested on synthetic data and finally, it has been applied to the aeromagnetic data of the Varzaghan area, and as a result, the location of faults in the area has been determined with high accuracy.

The potential-field gradient tensors are the second derivatives of potential-field data. Since the potential-field gradient tensor data contains nine signal components, their interpretation allows a high resolution and detailed investigation of geological structures. The methods based on the potential field gradient tensor (PGT) matrix use curvature or eigenvalue of the PGT matrix or directional methods of the PGT matrix. In the directional methods of the PGT matrix, in order to provide a more detailed map of the subsurface, Oruç and Keskinsezer (2008) have defined the directional tilt angles filters. Mikhailov et al. (2007) and Beiki (2010) have proposed the directional analytic signal to delineate the edges. However, this technique cannot display the edge of amplitude size of different anomalies simultaneously. Yuan and Yu (2015) have introduced second order directional analytic signal method and then, proposed a normalization method, which can display the large and small amplitude edges simultaneously. Yuan et al. (2016) have proposed horizontal directional theta (ED) method as an edge detection method based on the gravity gradient tensor that can weaken the above defects. It has higher resolution compared to the previous filters for delineating edges. However, for complex geological situations, the mentioned methods have some restrictions for edge detection. In this paper, to overcome these restrictions, NHM method has been proposed, and compared to other methods produces more detailed results.

The NHM is defined as follows: where HM is the horizontal modulus of the potential field gradient tensor and M is the modulus of potential field gradient tensor. The minimum value of NHM specifies the edges of magnetized structures. The NHM method beside tilt angle, total horizontal derivative of the tilt angle (THDR) and ED methods has been applied on synthetic magnetic data, and their results have compared. Moreover, the NHM is applied on aeromagnetic data from Varzeghan area.

The results of applying the tilt angle, THDR, and NHM methods on synthetic magnetic data have shown that the THDR method has been succeeded in determining the position of the bodies, however, the edges of the deeper bodies have not been recognized clearly. The tilt angle method can recognize the edges of the shallow and deep bodies simultaneously but with low accuracy. The ED method possesses high precision and high accuracy in identifying the edges, but in its results, some distortions can be observed. The NHM method of the total intensity data can display the edges of the bodies more accurately while no distortion is seen in the results of the NHM method. Therefore, the NHM filter, compared to other filters, produces more detailed results. The proposed method has been applied on the aeromagnetic data from Varzeghan area, and as a result, the recognized edges of the geological structures are found to be precise and clear.