Characterization of Heavy Oil Reservoir Using Vp/Vs Ratio and Neural Network Analysis

Abstract

The northeastern corner of Alberta contains an estimated 200 billion cubic metres of bitumen. Working interest partners Nexen Inc. and OPTI Canada Inc. hold rights to oil sands leases covering over 80,000 hectares in the Athabasca Oil Sands Region. The focus of this study is the southern portion of the Long Lake lease located approximately 40 km southeast of the City of Fort McMurray. The lease area is roughly 25,000 hectares and contains over 8 billion barrels of bitumen in place. It is well known, especially for heavy oil projects, that the Vp/Vs ratio is a good lithology discriminator. In this paper we provide Vp/Vs ratio volumes based on (i) deterministic prestack inversion and (ii) neural network analysis. From the prestack inversion the following volumes are estimated: P-impedance, Simpedance, density and Vp/Vs. The inversion approach accounts for the petrophysical relationship that exists in the logarithmic domain between: (1) P-impedance and S-impedance and (2) P-impedance and density. Neural network estimation of reservoir properties has proven effective in significantly improving accuracy and vertical resolution in the interpretation of the reservoir. Neural network analysis is performed on logs and pre-and post-stack seismic attributes. The Vp/Vs ratio volume from prestack inversion compared well with the similar volume obtained from neural network analysis. The latter results are sharper and offer more details in identification of the sand and shale within the heavy oil reservoir of Long Lake South.