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Continuous wavelet transform, theoretical aspects and application to aeromagnetic data at the Huanghua Depression, Dagang Oilfield, China
Author(s) -
Yang Yushan,
Li Yuanyuan,
Liu Tianyou
Publication year - 2010
Publication title -
geophysical prospecting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.735
H-Index - 79
eISSN - 1365-2478
pISSN - 0016-8025
DOI - 10.1111/j.1365-2478.2009.00847.x
Subject(s) - geology , wavelet , morlet wavelet , wavenumber , wavelet transform , geodesy , continuous wavelet transform , fourier transform , magnetization , magnetic anomaly , geophysics , seismology , discrete wavelet transform , mathematics , magnetic field , mathematical analysis , physics , computer science , optics , quantum mechanics , artificial intelligence
We use the continuous wavelet transform based on complex Morlet wavelets, which has been developed to estimate the source distribution of potential fields. For magnetic anomalies of adjacent sources, they always superimpose upon each other in space and wavenumber, making the identification of magnetic sources problematic. Therefore, a scale normalization factor, a − n , is introduced on the wavelet coefficients to improve resolution in the scalogram. By theoretical modelling, we set up an approximate linear relationship between the pseudo‐wavenumber and source depth. The influences of background field, random noise and magnetization inclination on the continuous wavelet transform of magnetic anomalies are also discussed and compared with the short‐time Fourier transform results. Synthetic examples indicate that the regional trend has little effect on our method, while the influence of random noise is mainly imposed on shallower sources with higher wavenumbers. The source horizontal position will be affected by the change of magnetization direction, whereas the source depth remains unchanged. After discussing the performance of our method by showing the results of various synthetic tests, we use this method on the aeromagnetic data of the Huanghua depression in central China to define the distribution of volcanic rocks. The spectrum slices in different scales are used to determine horizontal positions of volcanic rocks and their source depths are estimated from the modulus maxima of complex coefficients, which is in good accordance with drilling results.