Frequency-dependent AVO analysis: A potential seismic attribute for thin-bed identification

Abstract

Identifying thinly bedded reservoirs is important in exploration, appraisal, and development. The thin-beds we are referring to are of meter scale or less. Conventional seismic attributes are not able to resolve thin-bed effects. A new frequency-dependent amplitude-versus-offset (FAVO) seismic attribute is developed for the prediction of thin-beds. It is based on seismic wave scattering theory for vertically inhomogeneous media, where the seismic response from a laterally homogeneous interval is represented by the Born series. The Born series characterizes P-P and P-SV wave reflections, transmissions, and interbed multiples within the target interval with different order terms. The newly derived attribute corresponds to the second-order term of the Born series, where P-S wave reflection and transmission energy is taken into consideration, and it is named as the second-order FAVO gradient attribute. In a thinly bedded interval where sand/shale interfaces are abundant, the P-SV wave mode conversions are numerous. This leads to a strong second-order FAVO gradient attribute response compared to that of a blocky sand, silt, or shale interval under the assumption that there is no significant rock- and fluid- property differences between the intervals. Therefore, the new seismic attribute has the potential to be a thin-bed interval indicator. We propose a strategy to estimate the new attribute using conventional P-wave seismic data. The attribute is extracted from seismic data at the frequency range at which the second-order scattering effect is the most prominent. Synthetic and field data examples from offshore Trinidad are studied to demonstrate the second-order scattering effect and the potential usage of the second-order FAVO attribute for thin-bed reservoir characterization.

Amplitude Variation with Offset (AVO) Inversion for Reservoir Visualization: A Case Study of Taje Field, Niger Delta, Nigeria

“…In recent days, AVO analysis has been widely applied in hydrocarbon exploration studies [18][19][20][21][22] . In the Niger Delta, AVO techniques have been used to determine anomalous and gas zones in wells [23][24][25][26][27] , detect hydrocarbon reservoirs on pre-stack time seismic data [28] , and identify hydrocarbon-charged reservoirs using Rock physics modeling and Lamda-Mu-Rho (LMR) seismic inversion [28] .…”