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Sobel edge detection and its application in LMD-based seismic fault detection
KAI BAI1 ,
HUIQUN XU2,3 ,
XIAOYU SHE3
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1
School of Computer Science, Yangtze University, Jingzhou 434023, Hubei, P.R. China.,
2
Working Station for Postdoctoral Scientific Research, PetroChina Dagang Oilfield Company, Tianjin 300280, P.R. China.,
3
School of Geophysics and Oil Resources, Yangtze University, Wuhan 430100, Hubei, P.R. China.,
JSE 2018, 27(6), 531–542;
Submitted: 12 January 2018 | Accepted: 30 September 2018 | Published: 1 December 2018
© 2018 by the Authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract
Bai, K., Xu, H.Q. and She, X.Y., 2018. Sobel edge detection and its application in LMD-based seismic fault detection. Journal of Seismic Exploration, 27: 531-542. This paper aims to find a comprehensive method for detecting edges amidst background and noise. To this end, the local mean decomposition (LMD) filter and coherence algorithm were combined into a new seismic fault detection method. The priori knowledge on the edge location was calculated by the coherence cube, and the artificial edges were eliminated by the LMD filter. Then, the Sobel algorithm was adopted to obtain the greyscales based on the coherence, and derive the seismic edges. Through comparison, it is learned that the seismic edges obtained by our method coincide with the seismic faults in the original seismic data. Therefore, the proposed method can visualize seismic faults and accelerate the interpretation process. The research findings shed new light on the edge detection in relevant fields.
Keywords
local mean decomposition (LMD)
Sobel
edge detection
seismic fault detection
References
- Amstutz, S. and Fehrenbach, J., 2015. Edge detection using topological gradients: Ascale-space approach. J. Mathemat. Imag. Vis., 52: 249-266.doi:10.1007/s10851-015-0558-z
- Bahorich, M.S. and Farmer, S.L., 1995. 3D seismic discontinuity for faults andstratigraphic features: the coherence cube. The Leading Edge, 10: 1053-1058.doi: 10.1306/64eda3e8- 1724-1 1d7-8645000102c1865d
- Cai, C., Ding, M.Y., Zhou, C.P. and Zhang T.X., 2004. Composite edge detector basedon multi-wavelet operator. J. Image Graph., 9: 134-138. doi:10.11834/jig.20040222
- Carter, N. and Lines, L., 2001. Fault imaging using edge detection and coherencymeasures on Hibernia 3-D seismic data. The Leading Edge, 20: 64-69.doi:10.1190/1.1438880
- Chehrazi, A., Rahimpour-Bonab, H. and Rezaee, M.R., 2013. Seismic data conditioningand neural network-based attribute selection for enhanced fault detection. Petrol.Geosci., 19: 169-183. doi:10.1144/petgeo2011-001
- Cohen, L., 1989. Time-frequency distributions-a review. Proc. IEEE, 77: 941-981.doi:10.1109/5.30749
- Di, H. and Gao, D., 2014. Gray-level transformation and Canny edge detection for 3Dseismic discontinuity enhancement. Comput. Geosci., 72: 192-200.doi:10.1190/segam2013-1175.1
- Gersztenkorn, A. and Marfurt, K.J., 1999. Eigenstructure-based coherence computationsas an aid to 3-D structural and stratigraphic mapping. Geophysics, 64: 1468-1479.doi:10.1190/1.1444651
- Kanopoulos, N., Vasanthavada, N. and Baker, R.L., 2002. Design of an image edgedetection filter using the Sobel operator. IEEE J. Solid-State Circ., 23: 358-367.doi:10.1109/4.996
- Kitchen, L. and Rosenfeld, A., 2007. Edge evaluation using local edge coherence. IEEE
- Transact. Syst. Man Cybernet., 11: 597-605. doi:10.21236/adal09564
- KreSi¢-Jurié, S., 2012. Analysis of edge detection in bar code symbols: An overview andopen problems. J. Appl. Mathemat., 6: 1-16. doi:10.1155/2012/758657
- Luo, Y., Higgs, W. and Kowalik, W., 1996. Edge detection and stratigraphic analysisusing 3D seismic data. Expanded Abstr., 66th Ann. Internat. SEG Mtg., Denver:324-331. doi:10.1190/1.1826632
- Marfurt K.J., Kirlin, R.L., Farmer S.L. and Bahorich M.S., 1998. 3-D seismic attributesusing a semblance-based coherency algorithm. Geophysics, 63: 1150-1165.doi:10.1190/1.1444415
- Nadernejad, E., Sharifzadeh, S. and Hassanpour, H., 2008. Edge detection techniques:
- Evaluations and comparisons. Appl. Mathemat. Sci., 2: 1507-1520.
- Park, C., Looney, D., Hulle, M.M.V. and Mandic, D.P., 2011. The complex local meandecomposition. Neurocomput., 74: 867-875. doi:10.1016/j.neucom.2010.07.030
- Phillips, M. and Fomel, S., 2017. Plane-wave Sobel attribute for discontinuityenhancement in seismic images. Geophysics, 82: WB63-WB69.doi:10.1190/geo2017-0233.1
- Rashmi, Kumar, M. and Saxena, R., 2013. Algorithm and technique on various edgedetection: a survey. Sign. Image Process., 4: 65-75. doi:10.5121/sipij.2013.4306
- Smith, J.S., 2005. The local mean decomposition and its application to EEG perceptiondata. J. Roy. Soc. Interf., 2: 443-454. doi:10.1098/rsif.2005.0058
- Wang, W., Gao J., Li K., Ma K. and Zhang X., 2009. Structure-oriented Gaussian filterfor seismic detail preserving smoothing. IEEE Internat. Conf. Image Process.,601-604. doi:10.1109/icip.2009.5413869
- Xu, H.Q. and Gui, Z.X., 2011. Progress of Edge Detection Technology in Seismic
- Exploration. Special Oil & Gas Reservoirs, 18: 7-10.doi: 10.3969/j.issn. 1006-6535.201 1.04,002
- Ziou, D. and Tabbone, S., 1998. Edge Detection Techniques-An Overview. Internat. J.Pattern Recognit. Image Analys., 8: 537-559.
