Seismic-Q Compensation by Iterative Time-Domain Deconvolution

Abstract

Attenuation is often significant during seismic wave propagation in the subsurface, leading to the reduced resolution and narrower bandwidth of seismic images. Traditional corrections for such effects are inverse-Q filtering and deconvolution, which require a high signal-to-noise ratio (SNR) to avoid noise boost-up. Here, we propose a time-domain method offering advantages in the resolution and interpretational quality of the resulting images. Similar to wavelet transforms, the iterative time-domain deconvolution (ITD) represents the seismogram by a superposition of non-stationary source wavelets modeled in the appropriate attenuation model. Arbitrary frequency-dependent Q and velocity dispersion laws can be used and non-Q type attenuation can be caused by focusing, defocusing, scattering, effects of fine layering, and fluctuations of the wavefield. Compared to inverse-Q filtering and some deconvolution methods, the method does not boost high-frequency noise and is less sensitive to the accuracy of the Q model. We illustrate and compare this method to inverse-Q filtering by using several synthetic and real data examples. The tests include noise-contaminated data, inaccurate Q models, and variable source wavelets. The examples show that the ITD is a practical and effective tool for Q-compensation with a broad scope of potential applications, albeit with some defects. An important benefit of ITD that other methods may not possess could be the ability to utilize geological information, such as locations and sparseness of major reflectors or the presence of interpreted Q contrasts, which might be able to further improve the performance of ITD.