Delineation of Horizontal Locations and Estimation of Depth to Magnetic Source Geometries of Dubumbali, North-East Nigeria
Keywords:
Aeromagnetic Data, Wavelet Transform Technique (WTT), Euler Deconvolution Technique (EDT), Fourier Transform Technique (FTT), Magnetic Source GeometricsAbstract
Identification of magnetic source geometries of causative bodies is an important procedure when prospecting for hydrocarbon signatures from aeromagnetic data. In order to achieve this purpose, three methods namely Wavelet transform technique (WTT), Fourier transform technique (FTT) and Euler deconvolution technique (EDT) were applied to the reduced to equator (RTE) magnetic data. The WTT applied to the data is based on Morlet wavelet to determine the horizontal locations of magnetic source distribution in the potential field anomalies. These anomalies are always superimposed upon one another in frequency and space domain making it difficult to identify magnetic sources which are of adjacent sources. In view of this, each of the profile data was convoluted with the continuous wavelet transform and the square of coefficients from the convoluted profiles were plotted against the pseudo-wave number. Also, a scaled normalization factor was introduced on the coefficients so that the resolution of various adjacent magnetic sources can be revealed. Depth to magnetic sources was obtained using the FTT, while EDT is used to identify and estimate depth to various magnetic source geometrics with prescribed values of structural indices ranging from 1.0 to 3.0. From this analysis, we have been able to use both WTT and EDT to identify various magnetic source geometries which are attributed to volcanic intrusive rocks found to be predominant in the area while the results of depth estimate using both FTT and EDT ranges from 250 m to 1800 m. The study concluded that the methods are not only useful in the identification and estimation of source geometries due to magnetic anomalies alone, their combinations have served as a tool for identifying hydrocarbon signatures within the study area.
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