Inverse Stratigraphic Modeling Using Genetic Algorithms
Published:January 01, 1999
S. Bornholdt, U. Nordlund, H. Westphal, 1999. "Inverse Stratigraphic Modeling Using Genetic Algorithms", Numerical Experiments in Stratigraphy: Recent Advances in Stratigraphic and Sedimentologic Computer Simulations, John W. Harbaugh, W. Lynn Watney, Eugene C. Rankey, Rudy Slingerland, Robert H. Goldstein, Evan K. Franseen
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Stratigraphic modeling involves a multidimensional parameter fitting problem where a large number of free model parameters have to be adjusted for the model to match observational data. This task can be viewed as an optimization problem, which here is addressed using a genetic algorithm. The iterative trying-and-checking process, usually done manually, is thereby automated.
We apply this method for the automatic construction of sea level and subsidence curves for two simple toy models. We also address the problem of distinguishing the sea level variations vs. subsidence variations, and we give an example of a simulation involving carbonates from Mallorca, Spain.
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Numerical Experiments in Stratigraphy: Recent Advances in Stratigraphic and Sedimentologic Computer Simulations
Numerical Experiments in Stratigraphy: Recent Advances in Stratigraphic and Sedimentologic Computer Simulations - This volume presents the results derived from a three-day workshop held at the University of Kansas, Lawrence, Kansas, from May 15 through May 17, 1996. The objectives of the workshop were to document, characterize, demonstrate, and compare different computing procedures that have been utilized in simulating stratigraphic sequences. Both inverse and forward simulation modeling procedures are represented. The results of the workshop and the papers assembled here include: (1) an enhanced understanding of similarities and differences between models and modeling philosophies, (2) increased communication among modeling groups and geoscientists, (3) critical evaluation of applications and assessment of how models have been utilized, and (4) improvements and refinements in techniques for generating and describing model input and output.