Spectral decomposition based on multiple windows reassigned spectrum
Yuanyuan Ma, Zhen Cui, Dian Yuan, Siyuan Cao · 2016
Spectral decomposition decomposes a time-domain signal into a series of frequency components that can describe the characteristics of the local time-frequency (TF) properties and play an important role in seismic interpretation. However, the TF resolution of conventional spectral decomposition methods cannot meet the interpretation needs due to Heisenberg uncertainty principle. Furthermore, the energy of signals and random noise are mixed and can be hardly separated. We proposed the multiple window reassigned spectrum (MWRS) based on the orthogonal and recursive Hermite window function with the goal of improving the TF resolution, reducing the truncation error and dispersing the random noise. This method recombines a series of reassigned spectrums by the weighted value based on least square estimation. Simulated and field data results demonstrate that the proposed approach can locate the real position of TF energy precisely and indicate the low-frequency anomaly related with hydrocarbon effectively. Presentation Date: Tuesday, October 18, 2016 Start Time: 10:20:00 AM Location: 170/172 Presentation Type: ORAL