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Absorption compensation in seismic data processing Zhang, Changjun

Abstract

As seismic waves propagate through the earth, the anelasticity of the medium will cause energy dissipation and waveform distortion. This phenomenon is refereed to as absorption attenuation. High resolution images require that the effects of absorption are understood and estimated. Estimated attenuation parameters can be used to improve the interpretation of seismograms. For these reasons, absorption is an important topic in seismic data processing. The absorptive property of a medium is described by a quality factor which describes the energy decay and determines a velocity dispersion relationship. The quality factor and the velocity govern the propagation of seismic energy in the earth. Velocities determine the arrival times of reflections and quality factors determine their frequency contents. Both of them can be estimated from common mid-point (CMP) gathers. Quality factors can be estimated from prestack common midpoint gathers, or a poststack single trace. By assuming that the amplitude spectrum of the seismic source signature may be modeled by that of a Ricker wavelet, an analytical relation between a quality factor and the seismic data peak frequency variation with time has been derived. This relation plays a central role in quality factor estimation problems. Tests on both synthetic and real data show that the analytical relationship can be used to extract correct quality factors whether the data are one-dimensional or two-dimensional. To remove the effect of absorption, conventionally, inverse Q filtering is used. The stability of inverse Q filtering is always affected by high frequency noise whether it is implemented in the time or the frequency domain. Formulating the absorption compensation as an inverse problem, and solving the inverse problem iteratively, the resolution of seismic data is upgraded step by step. The inverse scheme helps to overcome the instability problem which is a natural drawback of common inverse Q filtering. Absorption compensation can also be considered as a part of the process of seismic data migration. Standard migration is the adjoint of forward modeling. High fidelity images can be obtained by using a least squares migration (LSM) scheme. Theoretical analysis shows that least squares migration is a promising way to implement migration and absorption compensation for a single processing step.

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