Abstract

Despite of high cost, seismic data have routinely been collected for oil sands development. While these data can be extremely valuable for the whole array of applications, including reservoir characterization, they are still, for the most part, largely underutilized. The main reason for the limited use of seismic in oil sands is the subtle sandstone-shale elastic differences and the lack of practical methods and techniques that make efficient use of the seismic information and mimic geophysical interpretation. In this paper, we present two novel approaches to deal with this challenge. The first approach works with 3D post-stack inverted seismic acoustic impedance data to derive facies trend models based on the local analysis of impedance geobodies. Too much impedance overlap between different facies that is observed globally and prevents efficient facies differentiation is resolved by extracting and analyzing objects from the 3D seismic volume that have local impedance contrasts. The second approach presents an optimization of empirical differential compaction calculations for the use in probabilistic 2D mapping of continuous/SAGD-able pay and its quality characteristics. Both approaches are shown to be straightforward and easy to implement into any software of choice. They are proven to lead to significant improvements in oil sands reservoir characterization based on a study of the Christina Lake and Kirby East leases of Cenovus Energy Inc.