Beamforming in Seismic Data Processing

Abstract

Minimum variance unbiased (MVU) beamforming is a type of multichannel filtering which extracts coherent signals without distortion, whilst minimising residual noise power. Adaptive beamforming estimates signal and noise characteristics as part of the extraction process. This paper gives the fundamental principle of beamforming including signal and noise model, design criteria and the obtained beamformer. The adaptive beamformer used here is designed from models of primary and multiple reflection signals having parametrically specified moveout, amplitude and phase variation with offset (MVO, AVO and PVO). However, PVO is not usually justified in practice. The resulting analysis provides data for input into AVO and PVO schemes for obtaining lithological information. Synthetic data examples illustrate details of implementation of parametric adaptive MVU beamforming and the response characteristics of the resultant design. Real data examples show that data‐adaptive beamforming is more flexible and more effective in attenuating multiples in prestack common mid point seismic data than Radon transform methods. In common with other prestack multichannel processes, the advantages of beamforming are shown to best effect in data with a good signal‐to‐noise ratio.

Attenuating Multiples in Seismic Data of Low Signal‐Tonoise Ratio using Optimal Beamforming

“…By definition MVU designs satisfy the general constraints: (1) No signal distortion; (2) Minimizing output coherent noise power. In order to attenuate coherent noise (multiples) while protecting all the information of the primaries, Hu et al [8] added two more constraints: (3) Null coherent noise; (4) control of random noise gain. They use data model of a seismic gather described in frequency domain as…”

“…White [7] introduced MVU beamforming to separate primaries and multiples from seismic data. Considering the AVO characteristics of seismic reflections, adaptive beamforming was developed by Hu et al [8] . They also gave some successful applications in 2-D seismic data processing [8,9] .…”

“…Considering the AVO characteristics of seismic reflections, adaptive beamforming was developed by Hu et al [8] . They also gave some successful applications in 2-D seismic data processing [8,9] . Hong et al [10] presented some good results about the study of the 3-D beamforming method.…”

SNR Improvement of Seismic Signals in Different Time Delays

“…In 2002, Jun Lin et al [5] developed a new electromagnetic source -phasedarray vibrator system (PAVS), which can generate directional wave and increase SNR of reflected signals. The alternative solution is processing data with optimal beamforming [6,7] or illumination analysis [8∼11] method.…”

An Adaptive Multiple Subtraction Algorithm Based on Independent Component Analysis

“…Multiple attenuation is a critical task in processing both marine and land seismic data for reducing the multiple contamination on true underground images which are typically constructed with primary reflections. The demultiple techniques can be divided into two major categories [1] : one is the filter method based on the difference between multiples and primaries [2,3] ; the other is the wave-equation based method which consists of multiple modelling and subtraction. The wave-equation based method can achieve good results and almost needs no prior information [4∼9] .…”