Tectonic modeling of Konya-Beysehir Region (Turkey) using cellular neural networks

D. Aydogan, O. Nuri Uçan, A. Muhittin Albora
2007 Annals of Geophysics  
In this paper, to separate regional-residual anomaly maps and to detect borders of buried geological bodies, we applied the Cellular Neural Network (CNN) approach to gravity and magnetic anomaly maps. CNN is a stochastic image processing technique, based optimization of templates, which imply relationships of neighborhood pixels in 2-Dimensional (2D) potential anomalies. Here, CNN performance in geophysics, tested by various synthetic examples and the results are compared to classical methods
more » ... classical methods such as boundary analysis and second vertical derivatives. After we obtained satisfactory results in synthetic models, we applied CNN to Bouguer anomaly map of Konya-Beysehir Region, which has complex tectonic structure with various fault combinations. We evaluated CNN outputs and 2D/3D models, which are constructed using forward and inversion methods. Then we presented a new tectonic structure of Konya-Beysehir Region. We have denoted (F1, F2, ..., F7) and (Konya1, Konya2) faults according to our evaluations of CNN outputs. Thus, we have concluded that CNN is a compromising stochastic image processing technique in geophysics.
doi:10.4401/ag-3060 doaj:c1fef821268844eea07b16712d11b978 fatcat:vpfr57prrrhctdqdgshdxfp2jq