Automatic selection of parameters for spectral decomposition of seismic data
V.D. Korchuganov1, A.V. Arefiev1, A.A. Lisin1
Novosibirsk State University, Novosibirsk, Russia
Keywords: 3D seismic exploration, spectral decomposition, RGB representation, differential evolution, spectrum approximation, Short-Time Fourier Transform (STFT)
Abstract
Spectral decomposition is a widely used method of qualitative seismic interpretation, whose key limitation lies in the subjective selection of frequency components for visualization. Existing approaches based on the analysis of the integral Fourier spectrum do not account for the temporal localization of the signal’s spectral content. This study introduces a new method for the automatic selection of frequencies based on approximating local spectra obtained via the Short-Time Fourier Transform (STFT) with a sum of three Morlet wavelet spectra. This approach enables the extraction of time-dependent frequency trajectories that capture the evolution of the signal’s spectral content, rather than relying on a static set of frequencies over the entire interval. The optimization problem is solved using the differential evolution algorithm. The method was tested on data from fields of the West Siberian petroleum province. Quantitative evaluation using Shannon and Rényi entropy metrics, as well as a colorfulness metric, demonstrated increased informativeness of RGB images compared with traditional approaches. The proposed method reduces interpretation subjectivity and ensures reproducibility of results.
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