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Abstract
Sarzalejo Silva, Sabrina E., and Bruce S. Hart,
DOI:10.1306/13371585St641173
2013 by The American Association of Petroleum Geologists.
Advanced Seismic-stratigraphic Imaging of Depositional Elements in a Lower Cretaceous (Mannville) Heavy Oil Reservoir, West-central Saskatchewan, Canada
Sabrina E. Sarzalejo Silva,1 Bruce S. Hart2
1Pacific Rubiales Energy, Calle 110 #9-25, Bogota, Colombia (e-mail: [email protected]); Previous address: Earth and Planetary Sciences Department, McGill University, 3450 University St., Montreal, Quebec, H3A 0E8, Canada.
2ConocoPhillips, 600 N. Dairy Ashford, Houston, Texas, 77079, U.S.A. (e-mail: [email protected]); Previous address: Earth and Planetary Sciences Department, McGill University, 3450 University St., Montreal,Quebec, H3A 0E8, Canada.
ACKNOWLEDGMENTS
Material presented in this chapter is derived from the Ph.D. dissertation of Sarzalejo Silva, undertaken at McGill University under the supervision of the senior author (Hart). We thank Nexen for providing the data used in this study and Landmark Graphics Corporation and Hampson-Russell for providing the software. Funding was provided by Nexen and the Natural Sciences and Engineering Research Council of Canada through an Industrial Partners grant.
ABSTRACT
We integrated core, wire-line logs, a three-dimensional (3-D) seismic volume, and a seismic attribute-derived 3-D lithology volume to define the stratigraphy of the Lower Cretaceous Mannville Group for a small area in Saskatchewan. The lithology volume was generated by integrating the seismic data with wire-line logs through the use of a probabilistic neural network. The stratigraphic interpretation was an iterative process: first, based on wire-line logs and cores; then, based on the integration of well
and 3-D seismic data; and finally, by integrating the attribute-derived lithology volume with the other data sets. Integration of the lithology volume into our stratigraphic interpretation, along with the exploitation of seismic-based visualization technologies, helped us to construct a better geologic model than what could have been constructed using only
well
data or conventional seismic-stratigraphic
analysis
techniques. Unfortunately, despite the high-frequency content (and good to excellent quality of the data), meter-scale variations of lithology in the primary reservoir interval could not be detected seismically because of the low acoustic-impedance contrasts between the various lithologies in this interval. Various types of noise in the seismic data also degraded the attribute-based property prediction.
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