Deghosting towed streamer data in τ/p domain based on rough sea surface reflectivity

Currently, the deghosting of towed streamer seismic data assumes a flat sea level and a sea-surface reflection coefficient of-1; this decreases the precision of deghosting. A new method that considers the rough sea surface is proposed to suppress ghost reflections. The proposed deghosting method obtains the rough sea surface reflection coefficient using Gaussian statistics, and calculates the optimized deghosting operator in the r/p domain. The proposed method is closer to the actual sea conditions, offers an improved deghosting operator, removes the ghost reflections from marine towed seismic data, widens the bandwidth and restores the low-frequency information, and finally improves the signal-to- noise ratio and resolution of the seismic data.

High-resolution frequency-domain Radon transform and variable-depth streamer data deghosting

Receiver ghost reflections adversely affect variable-depth streamer （VDS） data acquisition. In addition, the frequency notches caused by the interference between receiver ghosts and primary waves strongly affect seismic data processing and imaging. We developed a high-resolution Radon transform algorithm and used it to predict receiver ghosts from VDS data. The receiver ghost reflections are subtracted and removed from the raw data. We propose a forward Radon transform operator of VDS data in the frequency domain and, based on the ray paths of the receiver ghosts, we propose an inverse Radon transform operator. We apply the proposed methodology to model and field data with good results. We use matching and subtracting modules of commercially available seismic data processing software to remove the receiver ghosts. The frequency notches are compensated and the effective frequency bandwidth of the seismic data broadens.

Modeling of multi-depth slanted airgun source for deghosting

To obtain high-resolution of the subsurface structure, we modeled multidepth slanted airgun sources to attenuate the source ghost. By firing the guns in sequence according to their relative depths, such a source can build constructive primaries and destructive ghosts. To evaluate the attenuation of ghosts, the normalized squared error of the spectrum of the actual vs the expected signature is computed. We used a typical 680 cu.in airgun string and found via simulations that a depth interval of 1 or 1.5 m between airguns is optimum when considering deghosting performance and operational feasibility. When more subarrays are combined, preliminary simulations are necessary to determine the optimum depth combination. The frequency notches introduced by the excess use of subarrays may negatively affect the deghosting performance. Two or three slanted subarrays can be combined to remove the ghost effect. The sequence combination may partly affect deghosting but this can be eliminated by matched filtering. Directivity comparison shows that a multi-depth slanted source can significantly attenuate the notches and widen the energy transmission stability area.

New deghosting method based on generalized triangulation

A new deghosting method based on the generalized triangulation is presented. First, two intersection points corresponding to the emitter position are obtained by utilizing two azimuth angles and two elevation angles from two jammed 3-D radars （or 2-D passive sensors）. Then, hypothesis testing based deghosting method in the multiple target scenarios is proposed using the two intersection points. In order to analyze the performance of the proposed method, the correct association probability of the true targets and the incorrect association probability of the ghost targets are defined. Finally, the Monte Carlo simulations are given for the proposed method compared with the hinge angle method in the cases of both two and three radars. The simulation results show that the proposed method has better performance than the hinge angle method in three radars case.

Simultaneous receiver-side deghosting and denoising method based on the sparsity constraint

In marine seismic exploration,the sea surface ghost causes frequency notches and low-frequency loss,which aff ects the signal-to-noise ratio(SNR)and resolution of seismic records.This paper presents a simultaneous receiver-side deghosting and denoising method based on the sparsity constraint.First,considering the influence of propagation direction and sea surface reflection coefficient,the ghost time delay is calculated accurately,and then the accurate ghost operator is constructed in the frequency–slowness domain.Finally,the ghost-free data are obtained using the sparse constraint algorithm that can effectively suppress the ghost along with the noise energy.This method can remove the ghost and noise simultaneously,achieving quick convergence and with few iterations.It is applied to synthetic data and actual streamer fi eld data.Test results prove that the ghost and notches are suppressed eff ectively,the SNR is improved,and the band is well broadened.

A New Deghosting Algorithm with Hypothesis Testing Data Fusion

Eliminating the false intersection (deghosting) is a difficult problem in a passive cross location system. Using a decentralized decision fusion topology, a new deghosting algorithm derived from hypothesis testing theory is developed. It uses the difference between ghosts and true targets in the statistical error, which occurs between their projection angles on a deghosting sensor and is measured from a deghosting sensor, and constructs a corresponding test statistic. Under the Gaussian assumption, ghosts and true targets are decided and discriminated by Chi-square distribution. Simulation results show the feasibility of the algorithm.

An adaptive over/under data combination method

The traditional ＂dephase and sum＂ algorithms for over/under data combination estimate the ghost operator by assuming a calm sea surface. However, the real sea surface is typically rough, which invalidates the calm sea surface assumption. Hence, the traditional ＂dephase and sum＂ algorithms might produce poor-quality results in rough sea conditions. We propose an adaptive over/under data combination method, which adaptively estimates the amplitude spectrum of the ghost operator from the over/under data, and then over/under data combinations are implemented using the estimated ghost operators. A synthetic single shot gather is used to verify the performance of the proposed method in rough sea surface conditions and a real triple over/under dataset demonstrates the method performance.

Least-squares reverse-time migration for reflectivity imaging

A least-squares reverse-time migration scheme is presented for reflectivity imaging. Based on an accurate reflection modeling formula, this scheme produces amplitude-preserved stacked reflectivity images with zero phase. Spatial preconditioning, weighting and the Barzilai-Borwein method are applied to speed up the convergence of the least-squares inversion. In addition, this scheme compensates the effect of ghost waves to broaden the bandwidth of the reflectivity images. Furthermore, roughness penalty constraint is used to regularize the inversion, which in turn stabilizes inversion and removes high-wavenumber artifacts and mitigates spatial aliasing. The examples of synthetic and field datasets demonstrate the scheme can generate zerophase reflectivity images with broader bandwidth, higher resolution, fewer artifacts and more reliable amplitudes than conventional reverse-time migration.