Abstract

Seismic Amplitude Variation with Frequency (AVF) has emerged as an effective Direct Hydrocarbon Indicator (DHI), complementing traditional Amplitude Variation with Offset (AVO) methods. As seismic waves propagate through the subsurface, the presence of hydrocarbons such as oil or gas within porous rocks induces frequency-dependent attenuation, resulting in the progressive loss of highfrequency energy and a downward shift in the dominant seismic frequency (Batzle, M.L.,et al 2006). These effects are primarily attributed to intrinsic absorption and dispersion mechanisms in fluid-saturated rocks. By applying spectral decomposition techniques, AVF analysis enables the detection and mapping of these frequencydependent behaviors. Hydrocarbon bearing reservoirs typically exhibit low-frequency anomalies and increased amplitude attenuation at higher frequencies compared to surrounding nonreservoir rocks, an indicative response that can be validated with well log data. This study focuses on a shallow offshore field in the Krishna-Godavari (KG) Basin. Seismic data were decomposed using the S-transform to generate individual frequency gathers. From these, AVF attributes such as gradient (slope) and intercept were calculated based on the observed attenuation behavior. These attributes were then validated with seismic and well log datasets to evaluate their effectiveness. The results demonstrated that frequency-dependent amplitude variations can successfully distinguish between hydrocarbon and non-hydrocarbonbearing zones. This approach adds a new dimension to seismic interpretation workflows by contributing to exploration risk reduction. Overall, AVF-based analysis provides a fast and reliable qualitative method for hydrocarbon detection.