二代小波变换在重力场源分离中的应用

野外采集的重力数据是地下各类地质体重力场的叠加反映,如何有效地分离深源场和浅源场是重力资料处理中的一项重要内容。基于二代小波变换基本理论,在一维的基础上,给出了二维Haar预测算子的构造方法,并利用密度模型正演模拟,证明了二代小波变换实现多尺度分解的有效性,并以苏北某地区重力数据为例,应用二代小波变换开展浅部和深部重力异常场的分离。结果表明,该方法简单实用,在重力数据的场源分离中可以发挥重要的作用,对研究区域性断裂构造特征、划分构造单元、圈定隆坳格局等方面的地质问题具有参考价值。

Application of second-generation wavelet transform in the source separation of gravity field

The gravity data collected in field is a superposition reflection of the gravity field caused by various kinds of underground geological bodies. How to separate deep and shallow source field effectively is an important part of gravity data processing. According to the basic theory of second-generation wavelet transform, on the basis of the one-dimensional algorithm, this work determined the method of two-dimensional Haar prediction factors, and used the forward calculation of density model to validate the effectiveness of the second-generation wavelet transform for multi-scale decomposition. Finally, taking the gravity data in northern Jiangsu area as an example, this work separated shallow and deep gravity anomaly fields by using the second-generation wavelet transform. The results show that the method is simple and practical, and can play an important role in the separation of field sources of gravity data. It can provide important reference for the study of regional structural characteristics, the division of structural units, and the distribution of uplifts and depressions.