The application of genetic algorithms in structural seismic image interpretation

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Abstract

In this paper, we examine the applicability and repeatability of a genetic algorithm to automatically correlate horizons across faults in seismic data images. This problem arises from geological sciences where it is a subtask of structural interpretation of those images which has not been automated before. Because of the small amount of local information contained in seismic images, we developed a geological model in order to reduce interpretation uncertainties. The key problem is an optimisation task which cannot be solved exhaustively since it would cause exponential computational cost. Among stochastic methods, a genetic algorithm has been chosen to solve the application problem. Repeated application of the algorithm to four different faults delivered an acceptable solution in 94-100% of the experiments. The global optimum was equal to the geologically most plausible solution in three of the four cases. © Springer-Verlag Berlin Heidelberg 2002.

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Aurnhammer, M., & Tonnies, K. (2002). The application of genetic algorithms in structural seismic image interpretation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2449 LNCS, pp. 150–157). Springer Verlag. https://doi.org/10.1007/3-540-45783-6_19

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