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The AAPG/Datapages Combined Publications Database

AAPG Bulletin


AAPG Bulletin, V. 96, No. 2 (February 2012), P. 235–244.

Copyright copy2012. The American Association of Petroleum Geologists. All rights reserved.


Probabilistic correlation of single stratigraphic samples: A generalized approach for biostratigraphic data

Surangi W. Punyasena,1 Carlos Jaramillo,2 Felipe de la Parra,3 Yuelin Du4

1Department of Plant Biology, University of Illinois, 505 S. Goodwin Avenue, Urbana, Illinois 61801-3750; [email protected]
2Smithsonian Tropical Research Institute, Panama, Republic of Panama, P.O. Box 0843-03092, Panama; [email protected]
3Instituto Colombiano del Petroleo, Km 7 via Piedecuesta, Santander, Colombia; [email protected]
4Department of Electrical and Computer Engineering, University of Illinois, 1406 W. Green Street, Urbana, Illinois 61801-2918; [email protected]


Existing quantitative methods for biostratigraphic dating and correlation commonly ignore one of the key strengths of the microfossil record—relative abundance data. In this study, we present a maximum likelihood-based biostratigraphic method that demonstrates how microfossil abundance can be used in the stratigraphic placement of isolated samples. Precise correlation and dating of isolated paleontological samples is not possible with current methods, which are primarily intended for the alignment of longer stratigraphic sequences. In contrast, the probabilistic approach provided by likelihood analysis results in sample age estimates with defined confidence intervals. Therefore, all the uncertainties inherent in our age assessment (resulting from small sample sizes, incomplete sampling, imperfect knowledge of stratigraphic distributions, lack of taxonomic resolution of biostratigraphic data, and underlying environmental, paleogeographic, and sedimentologic processes) are explicit in our results. We conclude with a field test of the method, from data collected from an oil well from the Catatumbo Basin, Colombia, illustrating the use of our approach in a real-world case study and highlighting how our method could be generalized to a wide range of stratigraphic problems.

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