Separation of Magnetic Field Data Using 2-D Wavelet


UÇAN O. M., ŞEKER S., ALBORA A. M., ÖZMEN A.

EUROPEAN GEOPHYSICAL SOCIETY XXV GENERAL ASSEMBLY, France, 1 - 04 April 2000, vol.2, pp.1-2

  • Publication Type: Conference Paper / Summary Text
  • Volume: 2
  • Country: France
  • Page Numbers: pp.1-2
  • Istanbul University Affiliated: Yes

Abstract

The simplest is the graphical method in which a regional trend is drawn manually for profile data.  Determination of the trend is based upon interpreter’s   understanding understanding of the geology and related field distribution  This is a subjective approach  and  also  becomes  increasingly  difficult  with  large  2-D  data sets.  In the second approach, the regional field is estimated by least-squares fitting a low-order of the observed field .  This reduces subjectivity, but still needs to specify the order of the polynomial and to select the data points to be fit.  The third approach applies applies a digital filters such as Wiener filtering  to the observed .  In this study, one of the very update 2-D image processing technique, Wavelet approach is applied to magnetic anomaly map and satisfactory results are observed.  The scheme of separable 2-D processing, while simple and uses available 1-D filters, has disadvantages when compared to a genuine, 2-D MRA with non-separable filters. The latter possesses more freedom in design, can provide a better frequency and even linear phase response, and have non-rectangular sampling. In this paper, Wavelet approach has been used for magnetic field anomaly separation. The results obtained have been tested for synthetic  examples and satisfactory results are found.  This work was supported by Istanbul University Research Fund