Philippe Caprioli

Optimized deghosting of over/under towed-streamer data in the presence of noise

Seismic exploration is widely used to locate geologic formations for hydrocarbon accumulations. In a typical marine seismic survey, one or more marine seismic streamers are towed behind a survey vessel. As the streamers are towed, acoustic signals, commonly referred to as “shots,” are produced by the seismic source. These travel down through the water column into strata beneath the water bottom surface, where they are reflected from the various geologic formations and travel back to the sea surface. One well-known marine seismic problem is that these upgoing waves are then reflected with inverted polarity at the sea surface because of the air/water interface. Hence, the sensors in the seismic streamer cable record not only the desired wavefield (i.e., the upgoing wave-reflected signal from various subterranean geologic formations), but also their reflections from the sea surface (the downgoing wave). The undesired downgoing reflected signal is known as the “receiver ghost.” Depending on the incidence angl...

Surface multiple attenuation by up-down wavefield deconvolution: an OBC case study

Summary Multicomponent data allows the decomposition of the recorded pressure (P) and vertical component (Z) wavefields into upgoing and downgoing waves by a weighted summation of the two components recordings. It is well known that upgoing waves just below the sea bottom are free from water layer reverberations and receiver side surface multiples. This property is often used in P-Z summation. It is also well known that the deconvolution of the upgoing wavefield by the downgoing wavefield decomposed just above the sea bottom ideally eliminates all surface-related multiples. In this paper the up-down wavefield deconvolution method is briefly described and demonstrated with a multicomponent ocean bottom cable (OBC) dataset. The calibration of the vertical component recording is a prerequisite of wavefield decomposition and it is discussed first. Calibration A necessary prerequisite of pressure wavefield decomposition is the calibration of the Z component. It is generally assumed that the pressure component is properly calibrated and can be used as a reference to calibrate the vertical component. P-Z calibration aims to compensate for all differences between P and Z not related to wave propagation, such as spatially varying coupling effects. Since coupling is surface consistent P-Z calibration is usually performed in the common receiver gather domain. In this paper, calibration operators are considered as necessary processing filters. Attractive approaches to P-Z calibration use the acoustic wave equation, which only involves water properties: hence the possibility to reduce coupling perturbations. The two calibration methods used for this case study are summarized below.

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.

Robust dual-sensor data sea-surface ghost attenuation for quality control purposes: Robust receiver deghosting of dual-sensor data

Three-dimensional receiver ghost attenuation (deghosting) of dual-sensor towedstreamer data is straightforward, in principle. In its simplest form, it requires applying a three-dimensional frequency–wavenumber filter to the vertical component of the particle motion data to correct for the amplitude reduction on the vertical component of non-normal incidence plane waves before combining with the pressure data. More elaborate techniques use three-dimensional filters to both components before summation, for example, for ghost wavelet dephasing and mitigation of noise of different strengths on the individual components in optimum deghosting. The problem with all these techniques is, of course, that it is usually impossible to transform the data into the crossline wavenumber domain because of aliasing. Hence, usually, a two-dimensional version of deghosting is applied to the data in the frequency–inline wavenumber domain. We investigate going down the “dimensionality ladder” one more step to a one-dimensional weighted summation of the records of the collocated sensors to create an approximate deghosting procedure. We specifically consider amplitude-balancing weights computed via a standard automatic gain control before summation, reminiscent of a diversity stack of the dual-sensor recordings. This technique is independent of the actual streamer depth and insensitive to variations in the sea-surface reflection coefficient. The automatic gain control weights serve two purposes: (i) to approximately correct for the geometric amplitude loss of the Z data and (ii) to mitigate noise strength variations on the two components. Here, Z denotes the vertical component of the velocity of particle motion scaled by the seismic impedance of the near-sensor water volume. The weights are time-varying and can also be made frequency-band dependent, adapting better to frequency variations of the noise. The investigated process is a very robust, almost fully hands-off, approximate three-dimensional deghosting step for dual-sensor data, requiring no spatial filtering and no explicit estimates of noise power. We argue that this technique performs well in terms of ghost attenuation (albeit, not exact ghost removal) and balancing the signal-to-noise ratio in the output data. For instances where full three-dimensional receiver deghosting is the final product, the proposed technique is appropriate for efficient quality control of the data acquired and in aiding the parameterisation of the subsequent deghosting processing.

L1 Pseudo-Vz Estimation and Deghosting of Single-component Marine Towed-streamer Data

We present a novel technique to estimate the data of the vertical component of particle motion from marine single-component pressure data. The particle motion data, bar an angle dependent obliquity factor, is computed by convolution of the output from L1 deconvolution of the pressure ghost wavelet with the corresponding ghost wavelet of the particle motion. The estimated particle motion data is then used in a conventional two-component technique for receiver ghost attenuation by combination with the original pressure-wave data. We applied our technique to deep-tow streamer data of a 3D over/sparse-under marine survey, in which six streamers were towed at a shallow depth, with two further streamers towed deeper. This data set enables us to compare the results from our single-component deghosting technique with optimum deghosting of the over/sparse-under data. We will show that our technique achieves improvements in bandwidth of the single-component pressure data, while not fully reaching the quality of the optimally deghosted data from the over/sparse-under survey.