Ahmet Kemal Ozdemir

Combination of multi-component streamer pressure and vertical particle velocity: theory and application to data

Summary In this paper, we generalize the optimal deghosting (ODG) method used for deghosting over/under data to combine pressure (P) and vertical velocity (Z) data recorded with a 4C multi-component streamer to reduce the impact of the noise on the deghosted data. The ODG approach uses pressure and velocity ghost models and the statistics of the residual noise to minimize, in a least-squares sense, the noise on the up-going/deghosted wavefield. ODG and the standard PZ summation (PZSUM) combinations are applied to pressure and velocity data recorded in the North Sea (2-D acquisition). We show that both methods attenuate the receiver ghost, fill in information at the pressure notch frequencies and that ODG has the least postcombination noise level. We also show pre- and post-stack vertical velocity data with encouraging signal-to-noise ratios. Some differences between the ODG and PZSUM combination results can be explained using the cross-line component measurement. Finally, in order to further improve the PZ deghosted data, we suggest a toolbox approach that takes advantage of both ODG and PZSUM combinations and accounts for the varying signal-to-noise ratios observed on multi-component streamer data.

Mitigation of streamer noise impact in multicomponent streamer wavefield reconstruction

where ρ is the density of the medium. It is known (Linden, 1959) that the crossline component of the pressure gradient, Py, gives an important contribution in recovering from the cross-line aliasing, allowing the multi-channel reconstruction in the crossline direction of the seismic pressure. The MIMAP technique (Multichannel Interpolation by Matching Pursuit, Vassallo et al., 2010), has been proposed to exploit the anti-aliasing potential of two-component seismic data, P and Py, in realistic acquisition settings. It has also been discovered that the combined use of pressure, crossline and vertical component of the pressure gradient, P, Py and Pz, gives even more benefit, as it allows joint-interpolation and 3D deghosting of severely aliased data (Ozbek et al., 2010). Ozbek et al. (2010) introduced Generalized Matching Pursuit (GMP) as a technique to achieve this. Both MIMAP and GMP rely on the combination of measurements of different nature: in this paper we describe how this combination needs to take into account the differences between the signals and the noise characteristics that are observed on multicomponent marine measurements.

The optimal deghosting algorithm for broadband data combination

Data acquisition with concurrently towed shallow and deep streamers leads to deeper penetration and increased resolution. These benefits are achieved by using data processing algorithms that combine data acquired at different depths into a single dataset. However, the conventional algorithms used for this purpose do not consider the presence of noise. We present the optimal deghosting (ODG) algorithm which increases the bandwidth by optimizing the signal-to-noise ratio (SNR) of the combined data. The ODG algorithm estimates the statistics of the noise on shallow and deep streamers and minimizes the residual noise on the deghosted data in a least-squares sense. Hence, by optimally combining the data from streamers at different depths, the ODG method results in a broad bandwidth with enhanced low-frequency response and optimal SNR.

Efficient computation of joint fractional Fourier domain signal representation

A joint fractional domain signal representation is proposed based on an intuitive understanding from a time-frequency distribution of signals that designates the joint time and frequency energy content. The joint fractional signal representation (JFSR) of a signal is so designed that its projections onto the defining joint fractional Fourier domains give the modulus square of the fractional Fourier transform of the signal at the corresponding orders. We derive properties of the JFSR, including its relations to quadratic time-frequency representations and fractional Fourier transformations, which include the oblique projections of the JFSR. We present a fast algorithm to compute radial slices of the JFSR and the results are shown for various signals at different fractionally ordered domains.

Crossline Reconstruction Using Aliased 3D Deghosted Up- and Downgoing Wavefields

This paper formulates a new model for crossline reconstruction that relies on aliased, 3D decomposed, up- and downgoing waves. It also presents a closed form approach to solve the joint reconstruction and 3D deghosting problem. The new model provides additional insight into how the ghost reflection and the vertical component of particle velocity/acceleration are exploited in crossline reconstruction and joint 3D deghosting solutions for towed streamer applications.

Characterization and attenuation of transverse particle motion noise on multisensor point-receiver streamer

A multicomponent towed streamer measures both pressure and the particle velocity vector. The particle velocity vector enables us to calculate the 3D upgoing wavefield at any desired position within the aperture of the seismic spread and this allows improving not only the temporal bandwidth by removing ghost notches, but also the spatial bandwidth. However, particle motion sensors measure streamer-borne noise with amplitudes typically several orders of magnitude stronger than the corresponding noise recorded by hydrophones at frequencies below about 20 Hz. Therefore, stronger noise attenuation for particle velocity data is needed at these frequencies. In this paper, we introduce a multiscale noise attenuation algorithm that provides a high-fidelity particle motion measurement at frequencies down to 3 Hz.