Magnetic Field Interpretation Using Singular Value Decomposition Method Based on Correlation Coefficient of Eigenimages

Magnetic investigations can yield important information about geological structures. Singular Value Decomposition (SVD) is a very powerful tool for analysis of the geophysical data set chiefly potential fields. In this paper a new technique for demonstration of near- subsurface features with short wavelength using magnetic eigenvectors and eigenimage is proposed which separate the regional anomalies from magnetic map background. Also, is exhibited a new method based on correlation coefficient between eigenimages for threshold determination. Using the SVD, a matrix of magnetic data set can be decomposed to a series of eigenimages. Finally, the SVD method is eventuated two layers of two-dimensional singular value images that the layer reconstructed of threshold value to last eigenimages show local magnetic anomalies. The results obtained from the synthetic data set, with and without random noise, have been discussed. The method is demonstrated on real magnetic data set surveyed from Iran

کلیدواژه ها:

correlation coefficient ، eigenimage ، magnetic ، Singular Value Decomposition (SVD)