Edge detection is one of the most commonly used methods for the interpretation of potential field data, because it can highlight the horizontal inhomogeneous of underground geological bodies (faults, tectonic boundaries, etc.). A variety of edge detection methods have been reported in the literature, most of which are based on the combined transformation results of horizontal and vertical derivatives of the observations. Consequently, these edge detection methods are sensitive to noise. Therefore, noise reduction is desirable ahead of applying edge detection methods. However, the application of conventional filters smears discontinuities in the data to a certain extent, which would inevitably induce unfavourable influence on subsequent edge detection. To solve this problem, a novel edge-preserving smooth method for potential field data is proposed, which is based on the concept of guided filter developed for image processing. The new method substitutes each data point by a combination of a series of coefficients of linear functions. It was tested on synthetic model and real data, and the results showed that it can effectively smooth potential field data while preserving major structural and stratigraphic discontinuities. The obtained data from the new filter contain more obvious features of existing faults, which brings advantageous to further geological interpretations.

中文翻译：

---

一种势场数据的边缘辅助平滑方法

边缘检测是解释势场数据最常用的方法之一，因为它可以突出地下地质体（断层、构造边界等）的水平不均匀性。文献中报道了多种边缘检测方法，其中大部分是基于观测值的水平和垂直导数的组合变换结果。因此，这些边缘检测方法对噪声敏感。因此，在应用边缘检测方法之前需要降噪。然而，传统滤波器的应用在一定程度上涂抹了数据中的不连续性，不可避免地会对后续的边缘检测产生不利影响。为了解决这个问题，提出了一种新颖的位场数据保边平滑方法，它基于为图像处理而开发的引导滤波器的概念。新方法通过一系列线性函数系数的组合来替换每个数据点。在合成模型和真实数据上进行了测试，结果表明，它可以有效地平滑位场数据，同时保留主要的构造和地层不连续性。新滤波器获得的数据包含更明显的现有断层特征，有利于进一步的地质解释。结果表明，它可以有效地平滑位场数据，同时保留主要的构造和地层不连续性。新滤波器获得的数据包含更明显的现有断层特征，有利于进一步的地质解释。结果表明，它可以有效地平滑位场数据，同时保留主要的构造和地层不连续性。新滤波器获得的数据包含更明显的现有断层特征，有利于进一步的地质解释。