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AAPG Bulletin

Abstract

DOI:10.1306/09220403112

Stochastic surface-based modeling of turbidite lobes

Michael J. Pyrcz,1 Octavian Catuneanu,2 Clayton V. Deutsch3

1Quantitative Stratigraphy, ChevronTexaco Energy Technology Company, 4800 Fournace Place, Bellaire, Texas 77401; [email protected]
2Department of Earth and Atmospheric Sciences, University of Alberta, 1–26 Earth Sciences Building, Edmonton, Alberta, Canada T6G 2E3; [email protected]
3Department of Civil and Environmental Engineering, University of Alberta, 220 CEB Building, Edmonton, Alberta, Canada T6G 2E3; [email protected]

AUTHORS

Michael Pyrcz has just completed a Ph.D. at the School of Mining and Petroleum Engineering, Department of Civil and Environmental Engineering at the University of Alberta and has recently been hired by ChevronTexaco. Pyrcz has published several peer-reviewed technical papers and five papers in conference proceedings and has written a variety of geostatistical algorithms for deepwater and fluvial depositional settings.

Octavian Catuneanu is professor in the Department of Earth and Atmospheric Sciences at the University of Alberta, with a Ph.D. in geology from the University of Toronto. He is the recipient of a 2002 Best Paper Award of the Geological Society of America and a specialist in sedimentology, stratigraphy, and basin analysis. Catuneanu is the chair of the Canadian Sedimentology Research Group and a member of the North American and European Commission on Stratigraphic Nomenclature and Classification. He is the author of two textbooks and over 50 full-length, peerndashreviewed research and review articles and editor of several books and special volumes. Catuneanu is involved in a number of international research programs and is an instructor of sequence stratigraphy for conferences and companies from around the world.

Clayton Deutsch is a professor in the School of Mining and Petroleum Engineering, Department of Civil and Environmental Engineering at the University of Alberta. He teaches and conducts research into better ways to model heterogeneity and uncertainty in petroleum reservoirs. Deutsch has published 2 books, more than 70 peer-reviewed technical papers, and more than 70 papers in conference proceedings.

ACKNOWLEDGMENTS

We acknowledge the industrial supporters of the Center for Computational Geostatistics at the University of Alberta, the National Science and Engineering Research Council of Canada, and the Informatics Circle of Research Excellence in Alberta.

ABSTRACT

Flow event deposits in turbidite lobes are modeled with stochastic surface-based simulation. This method honors the geometries and compensational stacking of flow event deposits. Flow event deposit geometries are based on a flexible lobe parameterization. Compensational stacking is the tendency of flow event deposits to fill topographic lows and to smoothing of topographic relief. The surface-based model may be conditioned to well data.

Models of reservoir properties such as porosity and permeability are constrained by the resulting geometric models. This approach is applied in a geostatistical workflow to better integrate available geologic information. The resulting models may improve the accuracy of model reservoir response and account for the uncertainty in the heterogeneity of turbidite lobes.

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