Application of Constrained Least-Squares Spectral Analysis

Constrained Least-Squares Spectral Analysis (CLSSA) is applied to seismic data for (1) stratigraphic layer thickness estimation, (2) stratigraphic visualization, and (3) Hydrocarbon indication. Results obtained from these analyses are compared with similar analyses from Continuous Wavelet Transform (CWT) and Short Time Window Fourier Transform (STFT), to access improvements on time-frequency resolution associated with these analyses. Results from time frequency analysis of CLSSA spectrum, show apparent time thicknesses that strongly correlate with true stratigraphic thicknesses, demonstrated first from model data and then applied to real seismic data. Conversely, the spectrum of STFT shows underestimation of true stratigraphic thicknesses as a result of spectral smearing. Amplitude maps derived from analyzing the spectra of these methods show CLSSA to reveal more subtleness of hidden stratigraphic features in the seismic data as a result of high amplitude contrast between the stratigraphic features and the background. The spectrum of STFT suffers the limitation of poor amplitude contrast between the target feature and the background as a result of extraneous spectral energy smeared on the horizon. CWT shows a major setback arising from the duo temporal behavior within the data bandwidth. Analysis of CLSSA amplitude spectrum in hydrocarbon fluid-saturated porous medium also indicates strong anomalous amplitudes in the hydrocarbon zone with respect to background brine saturation comparative to CWT and STFT. These analyses demonstrate that spectral decomposition using CLSSA approach has superior time-frequency resolution to CWT and STFTEarth and Atmospheric Sciences, Department o