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An overview of wavelet estimation using free-surface multiple removal

ARCO, Plano, Texas, U.S.

Corresponding author: kmatson@mail.arco.com

The first 20% of the full text of this article appears below.

The goal of true-amplitude processing is to relate the measured seismic amplitudes to earth reflectivity in an absolute sense. A significant barrier to this longstanding objective has been the difficulty of estimating and removing the source effects from our seismic data. To illustrate the need for this, let us assume the simple model that the data contain reflection coefficients convolved with some source waveform. It is clear that we cannot properly analyze these reflection coefficients without first removing the phase and amplitude effects of the source. Fortunately, geophysicists have been able to extract much useful information through relative amplitude processing and will continue to do so in the future. However, the increasing demands placed on the fidelity of seismically derived information for tasks such as reservoir characterization heighten the need for better source wavelet estimation to bring us closer to processing absolute amplitudes.

Recent advances in free-surface multiple removal (FSMR) provide a significant step forward in realizing the goal of absolute-amplitude processing. In principle, the removal of free-surface multiples requires absolute measurements of the pressure field near the surface (for marine data application). Hence, the source wavelet must be known and effectively removed from the data for this process to be successful. Coupling the objective of free-surface multiple attenuation to the objective of wavelet estimation has provided newfound leverage in the wavelet-estimation problem. By using the multiple-attenuation machinery as a wavelet-estimation scheme, we can obtain estimates of the source wavelet in the water, independent of the subsurface. While significant, keep in mind that this represents only a first step toward absolute-amplitude processing since the earth invariably imparts some distortion/attenuation to the wavelet below the water bottom. In other words, this does not address the problem of estimating and deconvolving the wavelet at depth. This article gives an overview of some . . . [Full Text of this Article]