Introduction

A fundamental aspect of any seismic interpretation in which amplitudes are used to map reservoirs is the shape of the wavelet. This chapter presents introductory material relating to the nature of seismic wavelets; how they are defined, described and manipulated to improve interpretability. Seismic resolution, in terms of recognising the top and base of a rock layer, is controlled by wavelet properties. However, owing to the high spatial sampling of modern 3D seismic, resolution in the broadest sense also includes the detection of geological patterns and lineaments on amplitude and other attribute maps.

Seismic data: bandwidth and phase

The seismic trace is composed of energy that has a range of frequencies. Mathematical methods of Fourier analysis (e.g. Sheriff and Geldart, 1995) allow the decomposition of a signal into component sinusoidal waves, which in general have amplitude and phase that vary with the frequency of the component. An example is the seismic wavelet of Fig. 3.1, which can be formed by adding together an infinite set of sine waves with the correct relative amplitude and phase, of which a few representative examples are shown in the figure. The amplitude spectrum shows how the amplitude of the constituent sine waves varies with frequency. In Fig. 3.1 there is a smooth amplitude variation with a broad and fairly flat central peak. This is often the case as the acquisition and processing have been designed to achieve just such a spectrum. The bandwidth of the wavelet is usually described as the range of frequencies above a given amplitude threshold. With amplitudes that have been normalised, such as those shown in Fig. 3.1, a common threshold for describing bandwidth is half the maximum amplitude. In terms of the logarithmic decibel scale commonly used to present amplitude data this equates to −6 dB (i.e. 20 log10 0.5).