Roald van Borselen

Pressure wave-field deghosting for non-horizontal streamers

This abstract discusses a receiver deghosting method for seismic pressure wave-fields that have been recorded at arbitrary depth. For horizontal streamers, the deghosted pressure wavefield can be directly constructed from the scattered pressure wave-field in the spectral domain. For non-horizontal streamers, a system of equations is solved using a preconditioned conjugate gradient method. The mathematical derivation of the method is shown, and implementation issues are discussed. The effectiveness of the method is demonstrated using two synthetic examples.

Target-oriented adaptive subtraction in data-driven multiple removal

Data-driven multiple removal methods have proven a valuable addition to the demultiple toolbox for three main reasons. Firstly, such methods do not make use of any a priori information about the subsurface geology and, therefore, such information cannot bias the solutions. Secondly, data-driven methods can be applied in either 1D, 2D, or 3D mode and can therefore account for the full, multidimensional complexity of the earth. Finally, because no a priori information is used, the required user interaction is minimized. These methods are now applied in production-style processing environments with comparable speed and turn-around as conventional techniques.

Estimation of primaries by sparse inversion using dual-sensor data

Summary Most wave-equation based multiple removal methods, such as the surface-related multiple elimination (SRME) method, are based on prediction and subtraction of the multiples. Although this approach has proven successfully for many cases, it still shows some drawbacks such as handling missing near-offsets and distortion of primaries during the subtraction process. The recently introduced estimation of primaries by sparse inversion (EPSI) method estimates the primaries as unknowns in a multi-dimensional inversion process, where primaries are parameterized by spikes and a corresponding wavelet. Furthermore, it can reconstruct missing near offset data simultaneously. In this paper the EPSI method is extended to handle time-variant wavelet variations in the parameterization, which is necessary to obtain good results on field data. Because of the strong physical constraint between primaries and multiples, EPSI requires the upgoing wavefield at the surface. Therefore, it is very well suited for field data from a dual-sensor measurement, which provides a reliable upgoing wavefield.

An exploration‐scale wide azimuth towed streamer case study

Wide azimuth towed streamer surveys (WATS) have recently proven quite successful at improving illumination and attenuating multiple energy in difficult subsalt imaging environments. However, they present new challenges in terms of survey design, acquisition and processing methodology and operations. In particular, the sheer volume of data acquired requires pragmatic approaches to data processing. A 2007 deepwater Gulf of Mexico WATS survey of exploration scale (10,000 km2) illustrates these challenges and demonstrates the need for increased fold and cross-line offset.

Enhanced demultiple by 3D SRME using dual-sensor measurements

In recent years, dual-sensor recording has been introduced to marine seismic acquisition with reported benefits such as the increased bandwidth of the acquired seismic signal, improved signal-to-noise ratios due to deep-tow streamers, and operational efficiency due to an increased weather window.

Data regularization for 3-D SRME: A comparison of methods

Summary This paper discusses and compares different strategies for data regularization prior to the application of 3-D SRME. It is shown that synthetic analysis can be utilized to determine whether azimuth corrections are needed during data regularization. It is shown that only in certain instances this is needed, depending on the azimuth between the dipping reflectors and the acquisition direction. Also, the reflector dips, offset ranges and the reflectors depths are important. For geometries where azimuth corrections are needed, a comparison is made between two well-known solutions: Forward DMO followed by inverse DMO (DMO-DMO -1 ) regularization, and Fourier regularization with azimuth correction. It is shown that the latter shows better performance in terms of amplitude fidelity, as well as dealing with practical issues such as irregular sampling due to feathering of the streamers. Application of the Fourier regularization method to a field data set shows that the method is very capable of predicting complex 3-D multiples in the presence of multiple diffractions.

3D SRME: Acquisition & processing solutions

This paper describes the issues and possible solutions involved in the application of 3D data-driven multiple removal in a marine production environment. The optimization of marine data acquisition for 3D Surface related multiple elimination (SRME) is discussed. Recommendations for acquisition are given to create a dense grid of sail lines and streamers needed to predict the full 3D characteristics of the multiples. A processing sequence is discussed to predict and remove 3D multiples for each sail line using only the recorded data around the output streamer. The processing strategy does not rely on any a priori information or model of the subsurface to remove 3D multiples. The application of 3D SRME to a field data set from the Norwegian Sea leads to results that could not be obtained using its 2D equivalent.

Simultaneous Sources: A Controlled Experiment On Different Source Configurations

The simultaneous firing of marine sources can provide a significant uplift in terms of acquisition efficiency. However, the seismic interference resulting from one or more “other” sources needs to be well understood and the appropriate processing techniques need to be investigated. This paper uses the well known BP Wide-Azimuth Towed Streamer (WATS) synthetic dataset to carry out a controlled investigation into the effect of additional noise in 3D surface-related multiple elimination (SRME), depth migration and source separation. Two different simultaneous source configurations are considered: a front and tail and a side by side survey design. Results show that the front/tail configuration gives naturally cleaner results after 3D SRME and migration, but some source separation should always be applied; 3D SRME or migration alone isn’t enough to suppress the additional noise.

Enhanced 3D Surface Related Multiple Elimination with Dual-Sensor Data

In recent years dual-sensor recording has been introduced to marine seismic acquisition with reported benefits such as the increased band-width of the acquired seismic signal, improved signal-to-noise ratios due to deep-tow streamers, and operational efficiency due to an increased weather window. This abstract describes another advantage of dualsensor measurements, namely the opportunity it provides to better predict and subtract surface-related multiples from marine seismic data compared to using conventional data acquisition. Using a dataset from offshore Nigeria, it is demonstrated that dual-sensor acquisition leads to a more accurate set of predicted multiples with respect to phase and amplitudes. Consequently, the adaptive subtraction of the multiples can be carried out in a more constrained and robust manner, leading to better multiple elimination and better primary preservation.

A Conjugate Gradient Reconstruction of Missing Offsets

In seismic data processing, one is often confronted with incomplete spatial data due to practical limitations during data acquisition. Since many spatially-dependent seismic processing techniques require an extensive regular spatial support of the data, it is essential to reconstruct the missing data optimally. A new method is presented to reconstruct the missing sourceand receiver locations from the incomplete data itself, i.e. the incomplete data itself is used as reconstruction operator. The method requires no specific information about the subsurface (such as move-out properties). The only a priori information is the spatial band limitation of the data. It is shown that the reconstruction problem can be formulated as an integral equation that can be solved efficiently using a conjugate gradient iterative scheme. A numerical example is presented and discussed.