Frequency-dependent AVO analysis using the scattering response of a layered reservoir

Abstract

Sensitivity of reservoir properties to broadband seismic amplitudes can be weak, which makes interpretation ambiguous. Examples of challenging interpretation scenarios include distinguishing blocky reservoirs from fining sequences, low gas saturation from high gas saturation, and variable reservoir quality. Some of these rock and fluid changes might indicate stronger sensitivity to amplitudes over narrow frequency bands, which is a characteristic of frequency-dependent amplitude variation with offset (FAVO). We have developed a FAVO model for reservoir characterization, following a seismic scattering phenomenon through a set of isotropic elastic layers. The frequency dependency in our model comes from the time delays due to wave propagation within layers. The FAVO modeled response is a complex-valued amplitude varying with angle and frequency, and it is a function of the seismic velocities and thicknesses of individual layers, along with the conventional AVO response at all interfaces. Our FAVO seismic analysis consists of two main steps: (1) forward modeling using well logs to understand rock and fluid sensitivity to amplitudes to identify tuning frequencies with maximum amplitude excursions and (2) seismic analysis at tuning frequencies. With well-log models, we observed that the frequency-dependent tuning response is primarily dependent on the lithology stacking pattern of a reservoir; in the cases studied, the fluid and reservoir quality have secondary effects on the frequency dependence of the amplitudes. We evaluate synthetic models and field data from the Columbus Basin, Trinidad, to illustrate our frequency-dependent seismic analysis methods. For one of the sandstone reservoirs, a frequency-dependent attribute indicates better spatial resolution of the anomaly than a conventional amplitude extraction. FAVO attributes are complementary to conventional AVO attributes.

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] .…”

Estimation of porosity and gas hydrate saturation by inverting 2D seismic data using very fast simulated Annealing in the Krishna Godavari offshore basin, India

“…Several studies also determine various reservoir properties including porosity from seismic data using the geostatistical method, attribute analysis and inversion (e.g. Angeleri & Carpi, 1982; Doyen et al ., 1996; Pramanik et al ., 2004; Chopra & Marfurt, 2007; Kumar et al ., 2007, 2020; Ojha & Sain, 2007; Padhi & Mallick, 2013). However, to estimate gas hydrate saturation using the porosity estimated from the above‐said methods, we need to determine velocity or impedance along the seismic section separately.…”