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AAPG Bulletin

Abstract

AAPG Bulletin, V. 84, No. 10 (October 2000), P. 1617–1632.

Copyright ©2000. The American Association of Petroleum Geologists. All rights reserved.

Wavelet analysis of well-logging data from oil source rock, Egret Member, offshore eastern Canada

Andreas Prokoph,1 Frederik P. Agterberg2

1University of Ottawa, Department of Earth Science, P. O. Box 450, Stn. A, Ottawa, Ontario, K1N 6N5, Canada; email: [email protected]
2Geological Survey of Canada, 601 Booth Street, Ottawa, Ontario, K1A OE8, Canada; email: [email protected]

AUTHORS

Andreas Prokoph received his Ph.D. (1994) from the University Tübingen, Germany. He has been working at the GeoForschungszentrum Potsdam, Germany, and at the University College London, United Kingdom. Since 1996 he has been a postdoctoral scholar and part-time professor at the University of Ottawa, Canada. His research interests cover Cretaceous and Jurassic cyclostratigraphy, basin analysis, sedimentology, micropaleontology, and modeling and analysis of sedimentary patterns, seawater evolution, and the paleontological record.

Frederik "Frits" Agterberg obtained his Ph.D. in 1961 at the University of Utrecht in Holland. After a one-year postdoctoral fellowship at the University of Wisconsin, he joined the Geological Survey of Canada in Ottawa, where he headed the Geomathematics Section from 1971 to 1996 and is currently a senior scientist. His publications include the books Geomathematics (1974) and Automated Stratigraphic Correlation (1990). Since 1968 he has been associated with the University of Ottawa as an adjunct professor.

ACKNOWLEDGMENTS

We are grateful for the comprehensive data set provided by the Geological Survey of Canada (Atlantic) and for helpful discussions with Mark Williamson and Zehui Huang at the Bedford Institute of Oceanography in Dartmouth, Nova Scotia, to William K. Fyson (University of Ottawa) and Graeme Bonham-Carter (Geological Survey of Canada, Ottawa) for valuable suggestions on the final version of the manuscript. J. W. Schmoker, W. Yang, and an anonymous reviewer have given helpful comments and suggestions. Financial support was provided by the Geological Survey of Canada in Ottawa and the Deutsche Forschungsgemeinschaft (German Research Council) Grant Pr 545/1-1.

ABSTRACT

Wavelet analysis is a sensitive method for automatically detecting and Previous HitdistinguishingNext Hit abrupt Previous HitdiscontinuitiesNext Hit (i.e., faults, unconformities), cyclicity, and gradual changes in sedimentation rate by transforming depth-related sedimentary signals (i.e., gamma-rays) into wavelengths at distinct depth intervals. We used wavelet analysis for evaluation of the spatio-temporal distribution of oil source rocks and for estimating accumulation rates in a sedimentary basin having high resolution.

The method was applied to 16 gamma-ray logs from the Jurassic Egret Member (an oil–source rock succession 55 m to 227 m in thickness), offshore eastern Canada. Dominant gamma-ray cycles having wavelengths varying from 2.8 m (western margin of the basin) to 24 m (eastern part of the basin) have been detected by wavelet analysis. The coincidence of the ratio of predominant gamma-ray cycles with the ratio of Milankovitch spectra (about 400, 100, 40, 20 k.y.) suggests that climatic cycles are an important factor controlling sedimentary cyclicity in the Egret Member. Dominant wavelengths likely represent ~100 k.y. eccentricity, giving accumulation times of ~1.9 m.y. for stratigraphically complete sections having 19 successive 2.8 m gamma-ray cycles and giving accumulation times of ~600 k.y. for incomplete successions having only 6 cycles.

Up to four Previous HitdiscontinuitiesNext Hit occur in gamma-ray log cyclicity and separate the Egret Member into subunits. We interpret the Previous HitdiscontinuitiesTop as unconformities or faults and as related to sediments having low petroleum potential. The stratigraphic completeness of the Egret Member is correlated to total mass of organic carbon and decreasing thickness of non–source rock intervals, having correlation coefficients of r = 0.8 and r = –0.76, respectively. (Begin page 1618)

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