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Fusion Geophysical, Norman, Oklahoma, U.S.
Petróleos Mexicanos, Ciudad Pemex, Mexico
Corresponding author: mburnett@fusiongeo.com
| The first 20% of the full text of this article appears below. |
Recent reservoir studies involving spectral decomposition on various data sets from the Burgos and Macuspana basins of Mexico document the usefulness of this method as another way to uncover the effects of hydrocarbon accumulations on seismic data. Three such effects are illustrated in this article; attenuation of seismic waves passing through the reservoir, preferential reservoir illumination, and differential reservoir reflectivity.
Such phenomena can be clearly seen in these seismic studies only because of the use of a new method of spectral decomposition, the wavelet transform. Traditionally, spectral decomposition has used various techniques that require the use of a time window (e.g. Fast Fourier transform, discrete Fourier transform, maximum entropy, etc.). These windows produce serious distortion of true spectra and/or severely limit the vertical resolution; discrete spectral energy from individual reflection events that fall inside the window are mixed together, and when the window length is shortened to minimize this problem, frequency discrimination is compromised. Wavelet transforms, on the other hand, have no such windowing requirements and therefore avoid this distortion. Note that spectral decomposition, like inversion, is nonunique, but the wavelet transform generally does a vastly superior job of representing the individual wavelet spectra than windowed methods. This is the primary reason why analyses using the traditional techniques have been limited to map extractions. The windowed techniques do not preserve the individual reflection events and introduce distortions and artifacts. The ability to analyze the spectra of individual reflections is a major leap forward in the effectiveness of spectral decomposition.
| Burgos Basin studies |
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