Introduction

The variation of seismic reflection coefficients with offset can be used as a direct hydrocarbon indicator Ostrander (1984); Swan (1993), which is supported in the AVO analysis theory. AVO analysis requires previous prestack migration of the data, and velocity estimation is a key factor for this imaging problem. Velocity estimation affects the AVO response because it modifies the position of the events and the resulting amplitude values Grubb and Tura (1997). Because of the difficulty of estimating velocity models in complex areas, it is important to understand the sensitivity of AVO attributes to variation in velocity models. Mora and Biondi (1999) explore the relationship between velocity uncertainty and AVO-related seismic attributes using a real dataset. A conclusion from that work is that is important to investigate this problem using a synthetic model that allows more control over the data, which is needed to obtain a quantitative measure of the uncertainties.

In this work we do seismic modeling using typical rock properties from a real North Sea turbidite field. As is mentioned in Avseth et al. (1999), this field has been problematic because of complex sand distribution and non-reservoir sand anomalies. Two of the three most recent exploration wells failed to encounter reservoir sands in locations where poststack seismic amplitudes indicated reservoir sands. Avseth et al. (1999) suggest that AVO analysis in this field can help to discriminate sands from other lithofacies. However, because of the presence of complex velocity anomalies in the overburden, it is desirable to have a estimation of the uncertainty in the AVO response; in other words, how reliable is the lithology discrimination from AVO analysis given the presence of a complex overburden zone?

In this paper, we do forward modeling, simulating an earth model with an overburden that includes complex velocity anomalies. We generate several migration-velocity realizations by introducing coherent percentage velocity errors in the overburden zone of the original velocity model. We migrate the synthetic data using each velocity realization, and measure the variability in the resulting gradient and intercept AVO attributes that results from the velocity error.