Time-frequency decomposition can capture the nonstationary character of seismic data. In this paper, we propose a new method of time-frequency analysis based on regularized nonstationary autoregression coupled with Hilbert-Huang spectrum (RNARHHS). RNARHHS is an empirical-mode-decomposition like method but uses regularized nonstationary autoregression to construct its intrinsic mode functions (IMFs). Examples of synthetic and field seismic data show that this method achieves high time-frequency resolution and can detect low-frequency anomalies.

Presentation Date: Tuesday, October 18, 2016

Start Time: 8:00:00 AM

Location: 170/172

Presentation Type: ORAL

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