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AAPG Bulletin


AAPG Bulletin, V. 87, No. 4 (April 2003), P. 581-608.

Copyright 2003. The American Association of Petroleum Geologists. All rights reserved.

Log-curve amplitude slicing: Visualization of log data and depositional trends in the Middle Devonian Traverse Group, Michigan basin, United States

Albert S. Wylie Jr.,1 Jacqueline E. Huntoon2

1Department of Geological Engineering and Sciences, Michigan Technological University, 1400 Townsend Drive, Houghton, Michigan, 49931; email: [email protected]
2Department of Geological Engineering and Sciences, Michigan Technological University, 1400 Townsend Drive, Houghton, Michigan, 49931; email: [email protected]


Albert Wylie obtained a Ph.D. in geology in 2002 from Michigan Technological University where he developed the log-curve amplitude-slicing technique. He holds M.S. and B.S. degrees in geology from North Carolina State University. He has worked extensively in the areas of petroleum exploration and reservoir characterization in a variety of positions for companies including Gulf, Chevron, Santa Fe Energy, and Mobil.

Jacqueline Huntoon is an associate professor of geology at Michigan Technological University. She received her Ph.D. in geology from the Pennsylvania State University in 1990, her M.S. degree in geology from the University of Utah in 1985, and her B.S. degree in geology from University of California-Santa Cruz in 1981. She conducts a variety of basin-analysis studies that integrate surface and subsurface data with computer-based simulations of geologic processes.


We thank Carol Asiala for the Visual Basic programming and Lenny Mankowski for constructive discussions as the proportional slicing process evolved. We thank the reviewers, Robert Mitchum, Timothy Carr, and an anonymous reviewer for their helpful comments that resulted in the final manuscript. We also thank Jim Wood and Wayne Pennington for discussing the manuscript and suggesting ways to improve it. IHS Energy Log Services provided digital well logs. Schlumberger Information Solutions provided the Production Analyst program. LandMark Corporation provided the GeoGraphix mapping and cross section software. Michigan Technological University and the DeVleig Foundation supported this research, which constitutes part of Wylie's Ph.D. work. Parts of this research were supported by DOE contracts DE-AC26-98BC15100, DE-FC26-00BC15122, and DE-FC22-93BC14983 awarded to J. R. Wood at Michigan Technological University.


Well-log-curve shapes and amplitude trends are routinely used to correlate and map formations and reservoirs across petroleum basins or fields. However, the pattern-matching methods typically employed for correlation fail to make full use of the vertical resolution of well-log curves. A new technique, log-curve amplitude slicing, facilitates correlation by automating visualization of spatial trends in log-curve amplitudes. This new technique can be used with any type of log data that is sampled at a regular interval between two distinct correlated surfaces. The method generates a series of subhorizontal slices through the log curves that can be gridded and contoured to show trends and patterns in log-curve amplitudes in map view. The slices represent approximate time lines and are relative chronostratigraphic surfaces. When appropriate logs are used, the slices show the inferred distribution of lithofacies at the time of deposition. The evolution of an area can be investigated by stepping through a series of slices. Application of the log-curve amplitude-slicing technique facilitates correlation because it highlights trends that are not apparent using traditional methods to display and compare log curves.

As an example of the log-curve amplitude-slicing technique, gamma-ray log data are used in this article to analyze the evolution of the Michigan basin (United States) during deposition of the Middle Devonian Traverse Group. The Traverse Group consists mostly of carbonates, but the location, relative timing, and extent of significant fine-grained clastic influx to the basin is readily identifiable when the basin's history is reconstructed using the log-curve amplitude-slicing technique.

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