NDLI: Modelling Potential Field Sources in the Gelibolu Peninsula (Western Turkey) Using a Markov Random Field Approach

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Modelling Potential Field Sources in the Gelibolu Peninsula (Western Turkey) Using a Markov Random Field Approach

Content Provider	Springer Nature Link
Author	Albora, A. Muhittin Ucan, Osman N. Aydogan, Davut
Copyright Year	2007
Abstract	In this study, a Markov Random Field (MRF) approach is used to locate source boundary positions which are difficult to identify from Bouguer gravity and magnetic maps. As a generalized form of Markov Chains, the MRF approach is an unsupervised statistical model based algorithm and is applied to the analysis of images, particularly in the detection of visual patterns or textures. Here, we present a dynamic programming based on the MRF approach for boundary detection of noisy and super-positioned potential anomalies, which are produced by various geological structures. In the MRF method, gravity and magnetic maps are considered as two-dimensional (2-D) images with a matrix composed of N1 × N2 pixels. Each pixel value of the matrix is optimized in real time with no a priori processing by using two parameter sets; average steering vector (θ) and quantization level (M). They carry information about the correlation of neighboring pixels and the locality of their connections. We have chosen MRF as a processing approach for geophysical data since it is an unsupervised, efficient model for image enhancement, border detection and separation of 2-D potential anomalies. The main benefit of MRF is that an average steering vector and a quantization level are enough in evaluation of the potential anomaly maps. We have compared the MRF method to noise implemented synthetic potential field anomalies. After satisfactory results were found, the method has been applied to gravity and magnetic anomaly maps of Gelibolu Peninsula in Western Turkey. Here, we have observed Anafartalar thrust fault and another parallel fault northwest of Anafartalar thrust fault. We have modeled a geological structure including a lateral fault, which results in a higher susceptibility and anomaly amplitude increment. We have shown that the MRF method is effective to detect the broad-scale geological structures in the Gelibolu Peninsula, and thus to delineate the complex tectonic structure of Gelibolu Peninsula.
Starting Page	1057
Ending Page	1080
Page Count	24
File Format	PDF
ISSN	00334553
Journal	Pure and applied geophysics
Volume Number	164
Issue Number	5
e-ISSN	14209136
Language	English
Publisher	Birkhäuser-Verlag
Publisher Date	2007-01-01
Publisher Place	Basel
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Markov Random Field boundary analysis gravity and magnetic maps Gelibolu Peninsula Turkey Geophysics/Geodesy
Content Type	Text
Resource Type	Article
Subject	Geochemistry and Petrology Geophysics

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