An efficient and self‐adaptive approach for Q value optimization

Abstract

The time‐invariant gain‐limit‐constrained inverse Q‐filter can control the numerical instability of the inverse Q‐filter, but it often suppresses the high frequencies at later times and reduces the seismic resolution. To improve the seismic resolution and obtain high‐quality seismic data, we propose a self‐adaptive approach to optimize the Q value for the inverse Q‐filter amplitude compensation. The optimized Q value is self‐adaptive to the cutoff frequency of the effective frequency band for the seismic data, the gain limit of the inverse Q‐filter amplitude compensation, the inverse Q‐filter amplitude compensation function, and the medium quality factor. In the processing of the inverse Q‐filter amplitude compensation, the optimized Q value, corresponding gain limit, and amplitude compensation function are used simultaneously; then, the energy in the effective frequency band for the seismic data can be recovered, and the seismic resolution can be enhanced at all times. Furthermore, the small gain limit or time‐variant bandpass filter after the inverse Q‐filter amplitude compensation is considered to control the signal‐to‐noise ratio, and the time‐variant bandpass filter is based on the cutoff frequency of the effective frequency band for the seismic data. Synthetic and real data examples demonstrate that the self‐adaptive approach for Q value optimization is efficient, and the inverse Q‐filter amplitude compensation with the optimized Q value produces high‐resolution and low‐noise seismic data.

Extended Hilbert Transform and Application for Seismic Attributes

“…The real 3‐D seismic data used in this example were obtained by two steps. First, the original field 3‐D seismic data were acquired in China in 2006 by BGP, CNPC; we used the dynamite as the seismic source to generate seismic wavelet, and the time sample interval of the 3‐D seismic data is 1 ms. Then, we carried out signal processing to the original field 3‐D seismic data; the main processing methods include the static correction, noise attenuation, velocity analysis, high‐resolution processing such as the inverse Q ‐filtering (Zhang et al, , ) and deconvolution, and finally the seismic wave migration via seismic wave equation to obtain the 3‐D seismic data in time domain. HT, GHT, and EHT are carried out to the 3‐D seismic data in the time direction to generate the corresponding instantaneous amplitude and phase.…”