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The AAPG/Datapages Combined Publications Database

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Abstract

G. M. Grammer, P. M. ldquoMitchrdquo Harris, and G. P. Eberli, 2004, Integration of outcrop and modern analogs in reservoir modeling: AAPG Memoir 80, p. 45-66.

Copyright copy2004. The American Association of Petroleum Geologists. All rights reserved.

Predicting Tidal Sand Reservoir Architecture Using Data from Modern and Ancient Depositional Systems

Lesli J. Wood

Bureau of Economic Geology, John A. and Katherine G. Jackson School of Geosciences, University of Texas at Austin, Austin, Texas, U.S.A.

ACKNOWLEDGMENTS

This research was initiated as part of the Bureau of Economic Geology's Clastic Reservoirs Group, which included myself and project scientists Shirley P. Dutton, Chris D. White, and Brian Willis. Amoco Production, ARCO Oil and Gas, British Petroleum International, Chevron Petroleum Technology, Exxon Production, Intevep, Japan National Oil, Maxus Exploration, Oryx Energy, Saga Petroleum, and Statoil funded the research. Sharon Gabel, Matt Uliana, and Mulegheta Feseha assisted with data collection in the field, and Matt Uliana and Yugong Gao helped process the field data. Ramero Amaya and Dallas Dunlap helped load and quality control the well-log data, and Jana Robinson drafted the final figure. John C. Van Wagoner and Mark Kirschbaum generously provided advice and insights into the Sego deposition throughout the course of this project. Shirley Dutton provided early reviews that added significantly to the quality of the submission. Marjorie Levy, Bill Morgan, and Paul Harris provided comments and suggestions that immensely improved the quality of the final manuscript.

ABSTRACT

Tidal sandbanks make up most reservoir-quality rock volume in hydrocarbon fields characterized by tidally influenced deposits. Predicting the three-dimensional architecture and petrophysical character of these elements is critical to a proper assessment of a field's recoverable hydrocarbon potential. Most of these fields are under development or even in stages of secondary or tertiary recovery that require accurate flow-simulation and resource-distribution models.

Modern tidal settings and ancient tidal deposits provide dimensional and architectural data that can significantly reduce our uncertainty in constructing realistic reservoir models of these tidal-bank systems, improve our ability to estimate probability of exploration success, and help us evaluate correlation lengths between subsurface wells and lower-resolution seismic data. Modern tidal banks can be found in many depositional settings, from shallow estuaries to the outer continental shelf. Deep submarine canyons on the outer shelf strongly influence the shelf tidal processes by establishing a geomorphic link between deep-ocean and shallow-ocean currents. These interacting processes, in turn, influence the distribution of tidal banks. Banks that develop in shelf locations are thick, broad, and asymmetric, with linear forms distributed radially around the current or sediment source. Banks that develop in estuaries are thin, narrow, and symmetric, with parabolic forms or bar chains lying parallel to the estuary walls.

Ancient tidal banks from the Sego Sandstone (upper Campanian) in eastern Utah show a distinct organization of different dimensions between systems tracts and sequences. Falling-stage tidal bars and ridges are shorter and wider than transgressive tidal bars and ridges, a difference attributed to increased sediment supplies, decreased water depths, and increased energy conditions associated with base-level fall.

Cumulative-probability curves provide the format for using modern and ancient systems' architectural data on tidal-bank dimensions to estimate the probability that certain bank dimensions may occur in ancient deposits. Cumulative-probability curves show that the P50 for worldwide tidal-bank length is 12,000 m, width is 1600 m, and height is 9.2 m. These curves provide the means to assess the probability of correlation between wells of varying distances as well as the likelihood of resolving tidal banks in seismic data at varying resolutions.

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