Application of Fourier Transform and Signal Processing to Seismic Data Interpretation in the Niger Delta

This study applies Fourier transform methods and digital signal processing techniques to the interpretation of seismic reflection data in the Niger Delta sedimentary basin, South South Nigeria, one of the world's most petroliferous continental margins. Seismic data processing lies at the intersection of applied mathematics and petroleum geoscience, requiring advanced signal analysis skills for the extraction of subsurface structural and stratigraphic information from recorded acoustic wavefield data. The study focuses on post-stack seismic processing workflows applied to a 2D seismic survey dataset from an onshore Niger Delta prospect area, examining the mathematical operations of common depth point stacking, frequency filtering, deconvolution, and amplitude versus offset analysis from a signal processing perspective. Discrete Fourier transform analysis of seismic traces is used to characterise the frequency content of signal and noise components, providing the mathematical basis for designing optimal bandpass filters. The Wiener-Hopf deconvolution algorithm is derived from its minimum mean square error statistical foundations, and its application to wavelet compression and multiple reflection attenuation is demonstrated on the field dataset. Spectral decomposition using the short-time Fourier transform is applied to map seismic attribute anomalies associated with hydrocarbon-bearing reservoir intervals. Results demonstrate that frequency-domain processing significantly enhances the lateral continuity and vertical resolution of reflector imaging relative to unprocessed data. Keywords: Fourier transform, signal processing, seismic interpretation, Niger Delta, deconvolution