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Abstract

AAPG Bulletin, V. 87, No. 12 (December 2003), P. 1851-1868.

Copyright copy2003. The American Association of Petroleum Geologists. All rights reserved.

Geostatistical models for shales in distributary channel point bars (Ferron Sandstone, Utah): From ground-penetrating radar data to three-dimensional flow modeling

Hongmei Li,1 Christopher D. White2

1Craft and Hawkins Department of Petroleum Engineering, Louisiana State University, Baton Rouge, Louisiana 70803; [email protected]
2Craft and Hawkins Department of Petroleum Engineering, Louisiana State University, Baton Rouge, Louisiana 70803

AUTHORS

Hongmei Li received a B.S. degree from Jianghan Petroleum University, China, and an M.S. degree from the University of Petroleum, China, both in geology. She worked three years as a geologist for China Petroleum amp Chemical, China. In 2002, Li obtained an M.S. degree in petroleum engineering from Louisiana State University in the United States. Currently, she is employed as a reservoir geoscientist with Schlumberger.

Christopher White is an assistant professor of petroleum engineering at Louisiana State University. His research focuses on reservoir engineering, reservoir geology, and statistics. White was formerly a research scientist at the Bureau of Economic Geology and a senior research engineer with Shell Development. He earned his B.S. degree at the University of Oklahoma and his M.S. degree and Ph.D. at Stanford University, both in petroleum engineering.

ACKNOWLEDGMENTS

This project was funded by the U.S. Department of Energy under contract DE-FG02-01ER15167, with supplementary support from the Craft and Hawkins Department of Petroleum Engineering at Louisiana State University. The sedimentology of the Corbula Gulch site was interpreted by Rucsandra Corbeanu, under the supervision of Janok Bhattacharya at the University of Texas at Dallas. William S. Hammon and Robert Szerbiak of the University of Texas at Dallas interpreted and provided ground-penetrating radar data sets. George A. MecMechan and Xiaoxian Zeng of the University of Texas at Dallas provided constructive suggestion. Djuro Novakovic of Louisiana State University assisted with the reservoir simulation. Reviewers Brigitte Doligez, Joseph R. Studlick, and AAPG editor John Lorenz provided insightful and constructive reviews.

ABSTRACT

The hydraulic effects of shales on fluid flow in marine-influenced lower delta-plain distributary channel deposits are investigated using borehole, outcrop, and ground-penetrating radar data from the Cretaceous age Ferron Sandstone at Corbula Gulch in central Utah, United States. The instantaneous radar amplitude and gamma-ray counts are linearly correlated at well locations (rho = 0.84). This correlation is exploited to model shale occurrence throughout a 150 times 110 times 12-m-thick (492 times 361 times 39.4 ft) radar survey volume. Variograms of shale occurrence computed from radar data have a correlation range of 5–8 m (16.4–26.2 ft) with no significant areal anisotropy in shale dimensions. The radar-derived variograms are similar to variograms computed from outcrop data. Sequential Gaussian simulations create shale distributions on variably dipping accretionary surfaces. Flow simulations examine the effects of flow direction, variogram range, and shale coverage fraction on breakthrough time, sweep efficiency, and upscaled permeability. The flow simulations compare homogeneous and stochastic geologic models, flow in three coordinate directions, eight geostatistical parameter combinations, and five realizations for each combination of parameters. The effects of shales are modest compared to predictions based on earlier, two-dimensional studies of shales. Upscaled permeability is reduced by 2–11% (horizontally) and 42% (vertically). Compared to homogeneous models, the time to breakthrough is reduced by less than 5%. The effects on sweep efficiency are smaller. These results imply that simple models of point-bar accretionary shales may suffice for modeling analogous deposits in reservoirs. If detailed shale models are needed, the geostatistical parameters presented in this article can be used as a starting point for stochastic reservoir modeling.

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