DocumentCode :
178342
Title :
Fault detection in seismic datasets using hough transform
Author :
Zhen Wang ; AlRegib, Ghassan
Author_Institution :
Center for Energy & Geo Process. - CeGP, Georgia Inst. of Technol., Atlanta, GA, USA
fYear :
2014
fDate :
4-9 May 2014
Firstpage :
2372
Lastpage :
2376
Abstract :
In this paper, we present a semi-automatic algorithm to detect faults in seismic datasets using Hough transform. As a multistage approach, our method first highlights the likely fault points from the discontinuity map of one seismic section. Hough transform is then applied to detect faults features. Considering geological constraints of faults, false features are removed using a double-threshold method. Then, we get an initial fault line by connecting the remaining faults features. In the last stage, by incorporating the discontinuity information from step one, we tweak the initial fault line to obtain more accurate and reliable results. Our experimental results show that our method can delineate the fault lines in seismic sections more accurately than a state-of-the-art method.
Keywords :
Hough transforms; fault diagnosis; feature extraction; seismology; Hough transform; discontinuity map; fault detection; fault line; faults features; multistage approach; seismic datasets; seismic section; semi-automatic algorithm; Accuracy; Fault detection; Feature extraction; Geology; Joining processes; Reservoirs; Transforms; Hough transforms; fault detection; feature extraction; seismic imaging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location :
Florence
Type :
conf
DOI :
10.1109/ICASSP.2014.6854024
Filename :
6854024
Link To Document :
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