The use of multivariate statistical techniques for the analysis and display of AEM data
The use of multivariate statistical techniques for the analysis and display of AEM data
复制标题
DOI：
10.1071/eg998077
复制
发表时间：
1998-06
影响因子：
0.9
通讯作者：
A. Green
中科院分区：
文献类型：
--
作者：
A. Green
多个AEM通道的图像可以组合以产生RGB合成，该合成显示关于EM频谱（或其时域等效物）的形状的信息。AEM数据的高通道间相关性和宽动态范围意味着必须进行仔细的预处理，以提取数据中的所有有用信息。此外，虽然数据压缩技术，如主成分分析提供了很好的增强数据集内的可变性，它们产生的图像是难以与地球物理参数，如电导率和深度。这些限制可以通过对AEM数据进行非线性重新缩放来在一定程度上克服，以考虑从EM扩散过程的物理学产生的固有非线性关系。本文阐述了上述每一个问题，并讨论了新的处理方法来克服它们。
Images of multiple AEM channels can be combined to produce RGB composites that display information about the shape of the EM spectrum (or its time domain equivalent). The very high between-channel correlation, and the wide dynamic range of AEM data mean that careful preprocessing must be performed in order to extract all the useful information in the data. In addition, while data compression techniques such as Principal Components Analysis provide good enhancement of variability within the data set, they produce images that are difficult to relate to geophysical parameters such as conductivity and depth. These limitations can be overcome to some extent by non-linear rescaling on the AEM data to take into consideration the inherent non-linear relationships arising from the physics of the EM diffusion process. This paper illustrates each of the above problems and discusses new processing methods to overcome them.