Application of the normalized largest eigenvalue of structure tensor in the interpretation of potential field tensor data

Abstract

Obtaining horizontal edges and the buried depths of geological bodies, using potential field tensor data directly is an outstanding question. The largest eigenvalue of the structure tensor is one of the commonly used edge detectors for delineating the horizontal edges without depth information of the potential field tensor data. In this study, we presented a normalized largest eigenvalue of structure tensor method based on the normalized downward continuation (NDC) to invert the source location parameters without any priori information. To improve the stability and accuracy of the NDC calculation, the Chebyshev–Pade´ approximation downward continuation method was introduced to obtain the potential field data on different depth levels. The new approach was tested on various models data with and without noise, which validated that it can simultaneously obtain the horizontal edges and the buried depths of the geological bodies. The satisfactory results demonstrated that the normalized largest eigenvalue of structure tensor can describe the locations of geological sources and decrease the noise interference magnified by the downward continuation. Finally, the method was applied to the gravity data over the Humble salt dome in USA, and the near-bottom magnetic data over the Southwest Indian Ridge. The results show a good correspondence to the results of previous work. [Figure not available: see fulltext.]