We presented a few examples of application of an automated process designed to detect and track, in an accurate and objective way, reflections inside a recorded data set by exploiting their lateral phase continuity. The results, obtained in different profiles from both reflection seismic and GPR surveys, are quite accurate, since they are able to mark most of the recorded reflections and their different phases, with only a few exceptions in more complex areas characterized by noise or interference. Although the presented examples were limited to just 2D sections, the procedure can be easily extended to 3D data sets. A few input parameters must be selected and carefully evaluated by the interpreter, nevertheless the degree of subjectivity is greatly reduced with respect to other commonly used picking algorithms, leading to a faster and more objective process. Further improvements can be achieved by using integrated attributes as additional thresholds, or by evaluating the behavior of other physical parameters, such as changes in the spectral distribution.
Application of attribute-based automated picking to GPR and seismic surveys
DOSSI, MATTEO;FORTE, Emanuele;PIPAN, MICHELE
2015-01-01
Abstract
We presented a few examples of application of an automated process designed to detect and track, in an accurate and objective way, reflections inside a recorded data set by exploiting their lateral phase continuity. The results, obtained in different profiles from both reflection seismic and GPR surveys, are quite accurate, since they are able to mark most of the recorded reflections and their different phases, with only a few exceptions in more complex areas characterized by noise or interference. Although the presented examples were limited to just 2D sections, the procedure can be easily extended to 3D data sets. A few input parameters must be selected and carefully evaluated by the interpreter, nevertheless the degree of subjectivity is greatly reduced with respect to other commonly used picking algorithms, leading to a faster and more objective process. Further improvements can be achieved by using integrated attributes as additional thresholds, or by evaluating the behavior of other physical parameters, such as changes in the spectral distribution.File | Dimensione | Formato | |
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Dossi et al. 2015 - GNGTS.pdf
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