Examination of wide‐angle, multi‐component, AVO attributes for prediction of shale in heavy oil sands: A case study from the Long Lake Project, Alberta, Canada

Abstract

Summary A fundamental geologic problem in the Steam-Assisted Gravity Drainage (SAGD) heavy oil developments in the McMurray formation of Northern Alberta is to determine the location of shales in the reservoirs that may interfere with the SAGD process. Petrophysical analysis shows that a key indicator of the presence of shale in the Long Lake Project is bulk density. In theory, density can be derived from seismic data using Amplitude Versus Offset (AVO) analysis of conventional and/or multi-component seismic data, but this is not widely accepted in practice. However, with billions of dollars slated for SAGD developments in the upcoming years, this technology warrants further investigation. In addition, many attributes can be investigated using modern tools like neural networks; so, the density extracted from seismic using AVO can be compared and combined with more conventional attributes in solving this problem. Results to date show a strong correlation of the density derived using AVO to that measured by the bulk density logs in the wells. The P-impedance also shows an expected correlation to both the presence of shales and to the density attribute. Further work is being done to combine the various attributes derived to date in a neural network for the direct prediction of the Gamma Ray (GR) log.