Polarization filtering has been widely used to enhance signal-to-noise ratios for multicomponent seismic data. Polarization filters routinely depend on the ellipticity and directionality of spatial particle motions. However, factors such as noise and formation heterogeneity often make the polarization characteristics of body waves hard to distinguish. Here, we introduce a technique in the time domain for the separation of valid body waves and noise based on wave vector characteristics. First, we characterise the ground-roll polarization by the median wave vectors derived in large-scale moving time windows. For the suppression of ground roll, we fit the particle trajectory of ground roll by the least square method using all components simultaneously. Second, we apply three-stage smoothing to the ground-roll-removed multicomponent records. In each stage, we use mean or median vectors derived in small-scale moving-time or moving-trace windows to attenuate random noise and other non-ground-roll related coherent noise. The filter in the proposed method is not devised according to ellipticity and directionality. Instead, we use the wave vector decomposition to distinguish between noise and valid signals. Synthetic data and field data examples confirm that the proposed method can effectively suppress noise without damaging the high and low frequencies of a valid signal.

Amplitude variation with incidence angle (AVA) or amplitude variation with offset (AVO) inversion provides remarkable information in discriminating lithology in hydrocarbon reservoirs. Fluid parameters (e.g., porosity, water and oil saturations) are normally obtained through two steps and hard to get from seismic data directly and accurately. Theoretically, the exact Zoeppritz equations and Biot-Gassmann equations can be combined together to invert fluid parameters using seismic data directly. In this paper, AVA inversion is carried out to invert porosity, water and oil saturations from seismic data using the exact Zoeppritz equations and accurate estimation of Jacobian matrix. This matrix is composed of the partial derivatives of P- and S-wave reflection coefficients with respect to fluid parameters. Characteristics of these partial derivatives are analyzed in this study. In addition, the iterative equations for AVA inversion is derived based on the Taylor series expansion. The numerical tests show that this proposed algorithm can invert fluid parameters directly and accurately using seismic gathers. Unlike the conventional AVA using the approximations, the inversion using the exact Zoeppritz equations and accurate estimation of Jacobian matrix is not limited by the selection of incidence angles and reflection interfaces. This method is also applicable to seismic data collected from formations with strong elastic contrast interfaces or large incidences angles.