Edge detection of the sources of potential field anomaly is an important step in the interpretation of subsurface source geometries. The conventional methods based on calculation of horizontal or vertical derivatives identify the edges or center of sources by minima, maxima, or zero values in the transformed data. We present a wavelet source edge detector method (WSED) using wavelet multiresolution analysis to identify potential field sources boundaries. The two-dimensional wavelet decomposition is an effective method to understand the frequency components of the signal in different directions. We use a 2D-discrete wavelet transform using Haar wavelets in resolving lateral edges for source edge detection. We test the method on synthetic magnetic anomalies due to sources of complex geometries generated using prismatic sources. We investigated the robustness of the method on the magnetic data of the Bishop model and found the results useful in resolving the edges. We applied the method to gravity data of the north Delhi fold belt, India, to identify boundaries of different geological formations. Our results indicate distinct properties of the source edges in the wavelet domain, which is for the first time reported for the interpretation of the potential field anomalies.

潜在场异常源的边缘检测是解释地下源几何形状的重要步骤。基于水平或垂直导数计算的常规方法通过转换数据中的最小值，最大值或零值来标识源的边缘或中心。我们提出了一种使用小波多分辨率分析的小波源边缘检测器方法（WSED），以识别潜在的场源边界。二维小波分解是一种了解信号在不同方向上的频率分量的有效方法。我们使用Haar小波使用二维离散小波变换来解析横向边缘以进行源边缘检测。由于使用棱柱形源生成的复杂几何形状的源，我们对合成磁异常测试了该方法。我们对Bishop模型的磁数据研究了该方法的鲁棒性，发现结果对于解决边缘很有用。我们将该方法应用于印度北德里褶皱带的重力数据，以识别不同地质构造的边界。我们的结果表明小波域中源边缘的不同属性，这是首次报道用于解释潜在场异常。