--> Abstract: Predicting Thin-Bed Thickness Using Amplitude-Versus-Frequency Analysis, by Hongliu Zeng; #90082 (2008)

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Predicting Thin-Bed Thickness Using Amplitude-Versus-Frequency Analysis

Hongliu Zeng
BEG, University of Texas at Austin, Austin, TX

An amplitude-versus-thickness (AVT) curve has been used to predict thickness of seismically thin beds since the 1970’s. With a Rickerlike wavelet, the composite amplitude from a thin bed will increase with thickness, reaching a maximum of λ/4, and then decrease with thickness. The AVT relationship below λ/4 is almost linear, making it possible to calculate thickness of a thin bed without visually resolving its top and base.

However, to reveal an AVT relationship, interpreters have to measure thin-bed thicknesses and amplitude values at multiple wells. They also have to assume consistent impedance contrasts for all thin beds in the study area, implying consistent lithology, porosity, and fluid condition at all well locations. In many fields, such conditions are not satisfied, and thickness prediction using AVT can be erroneous.

An amplitude-thickness relationship can be expanded by investigating the frequency dependency of AVT. Processing tools include digital panel filtering, wavelet transform, or spectral decomposition. By separating and displaying seismic traces in different frequency bands, interpreters may see different AVT’s with variable tuning points. A reorganization of these AVT’s offers interpreters a unique way of analyzing an amplitude-thickness relationship from a different perspective. For a bed of fixed thickness, amplitude increases and then decreases with the dominant frequency, with maximum amplitude being reached at the tuning frequency. This relationship is called amplitude versus frequency, or AVF.

Armed with AVF, interpreters can analyze amplitude-thickness relationships using a single data trace. The method is suitable for reservoirs of multiple lithologies (conglomerate, sandstone, siltstone, etc.) and variable fluids (gas, oil, brine, CO2, etc.). Both model and field data examples will be presented to support the conclusion.

AAPG International Conference and Exhibition, Cape Town, South Africa 2008 © AAPG Search and Discovery