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The AAPG/Datapages Combined Publications Database
AAPG Bulletin
Abstract
AAPG Bulletin, V.
A method for assessing statistical significance and uncertainties for calibration of 1-D thermal basin maturation models
S. Noeth,1 R. O. Thomsen,2 R. Littke3
1Department of Geology and Geophysics, MT Halbouty Building, Texas A&M University, College Station, Texas, 77843-3115; [email protected]; second address: Institute of Geology, University of Cologne, Zulpicher Straße 49a D-50674 K?ln, Germany; email: [email protected]
2Department of Geology and Geophysics, MT Halbouty Building, Texas A&M University, College Station, Texas, 77843-3115; email: [email protected]
3Institute of Geology and Geochemistry of Petroleum and Coal, Aachen University of Technology (RWTH), Lochnerstraße 4-20 D-52056 Aachen, Germany; email: [email protected]
AUTHORS
Sheila Noeth is a geologist and visiting assistant professor at Texas A&M University, where she has been working as a postdoctoral researcher since 1999. She received her doctorate from the University of Bochum, Germany, in 1991 and joined the Organic Geochemistry and Environmental Geology group at the University of Cologne, where she worked as an assistant professor to complete her Habilitation. Her interests are focused on basin modeling, petroleum geology, and quantitative assessments of uncertainties related to numerical modeling.
Rene O. Thomsen is a geologist and professor at Texas A&M University, where he heads the Petroleum Studies Group. He received his Ph.D. from the University of South Carolina in 1990. His professional experience ranges from university to oil company and oilfield service companies. Since 1986 his research has been on development and use of integrated quantitative analysis in petroleum geology with emphasis on process understanding and simulation, basin modeling in its broadest sense, and integration of geodisciplines for quantitative assessments.
Ralf Littke is a geologist and professor at Aachen University of Technology (RWTH Aachen), Germany, where he leads the Institute of Geology and Geochemistry of Petroleum and Coal. In 1985, he received a doctorate from the University of Bochum, where he also completed his Habilitation in 1993. From 1985 to 1997 he worked as a research scientist at the Institute of Petroleum and Organic Geochemistry at the Research Center Julich. Currently, his interests in petroleum geology include basin modeling, the origin of organic and inorganic gases in the upper crust, and sedimentation processes.
ACKNOWLEDGMENTS
We wish to thank the German Research Foundation for financial support, the Petroleum Studies Group at Texas A&M University for fruitful discussions, and the reviewers, Jerry Sweeney and Ed Colling, for their encouraging comments that helped put the manuscript into its final form.
ABSTRACT
Basin modeling as a quantitative tool in petroleum studies necessarily implies knowledge about the limiting factors of the model, especially because modeling methods are widely used when ranking 
exploration
targets and assessing associated geologic risk. Commonly, model validity is checked by time-consuming (trial and error) calibrations against measured data, attempting complicated modifications of the model to satisfy the highly nonlinear relationships between model parameters. These procedures can result in an overinterpretation of model results. Inversion procedures, however, aim at finding the simplest set of model parameters that best agree with calibration data, taking the known uncertainties into account. In this article, an easy to use and rapid pseudoinverse method is presented for one-dimensional (1-D) deterministic forward models. By assessing uncertainties and some measure of the goodness of fit to observed data, in this case vitrinite reflectance, the significance of variations of different input parameters can be rapidly evaluated. The method is illustrated on a data set from a detailed 1-D modeling study of a small region of the German Variscan Rhenish massif. The significance and uncertainties of the two main parameters affecting vitrinite reflectance, that is, heat flow and burial depth during maximum burial, are assessed and discussed. Besides using real data, a theoretical approach is presented, by approximating the residual surface using a polynomial or cubic spline interpolation for a few data points only. The resolution limits, sensitivity, and uncertainty can be easily assessed, and the residual surface can be converted to a pseudoprobability density function for use in later risking procedures.
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