Boundary interpretation of gravity gradient tensor data by enhanced directional total horizontal derivatives

Abstract:

Boundary identification is a requested task in the interpretation of potential-field data, which has been widely used as a tool in exploration technologies for mineral resources. The main geological edges are fault lines and the borders of geological or rock bodies of different density, magnetic nature, and so on. Gravity gradient tensor data have been widely used in geophysical exploration for its large amount of information and containing higher frequency signals than gravity data, which can be used to delineate small scale anomalies. Therefore, combining multiple components of gradient tensor data to interpret gravity gradient tensor data is a challenge. This needs to develop new edge detector to process the gravity gradient tensor data. In order to make use of multiple components information, we first define directional total horizontal derivatives and enhanced directional total horizontal derivatives and use them to define new edge detectors. In order to display the edges of different amplitudes anomalies simultaneously, we present a normalization method. These methods have been tested on synthetic data to verify that the new methods can delineate the edges of different amplitude anomalies clearly and avoid bringing additional false edges when anomalies contain both positive and negative anomalies. Finally, we apply these methods to real full gravity gradient tensor data in St. Georges Bay, Canada, which get well results.