Identification of the typical frequency range associated with subsurface gas zones: a study using Hilbert-Huang transform and wavelet analysis

Abstract

Frequency attributes embedded in nonlinear geophysical signals such as well-log data or seismic data can provide vital clues in the effective characterization of the subsurface reservoir. Therefore, it is always important to recognize suitable mathematical techniques that need to be employed to extract such vital information from the nonlinear geophysical data. Several nonlinear mathematical techniques include wavelet analysis, fractal and multifractal analyses, and the fully data-adaptive Hilbert-Huang transform (HHT) technique. In the present study, we employ the HHT and the wavelet analysis techniques to seismic data of the Dutch sector of southern North Sea. We use a small portion of the seismic data, consisting of inline section 133 and time slice section 520 ms of the F3 block, to extract the instantaneous frequency associated with the subsurface gas zone. HHT constitutes two independent techniques, namely, the empirical mode decomposition (EMD) technique and the Hilbert spectral analysis (HSA). While the EMD technique facilitates to decompose the data into different signals of varied frequencies, called intrinsic mode functions (IMFs), the HSA helps to determine the instantaneous amplitudes and frequencies of the IMFs. EMD technique, together with HSA, has delineated a low-frequency spectral signature, believed to be a subsurface gas zone in the chosen data, corroborating the results of earlier studies of the same data sets. The instantaneous frequency range of the gas zone estimated by HSA was validated with the two-dimensional continuous wavelet transform (CWT) of the data sets using a suitable frequency range of Morlet wavelet. Results of the combined HHT and CWT analyses confirmed that the subsurface gas zone could be well identified in the frequency range 14–18 Hz. Results have direct implications in situ, in the sense that, by performing CWT analysis of seismic data using a Morlet wavelet in the frequency range 14–18 Hz, one can easily identify the location of subsurface gas zones.