Channel edge detection using 2D complex shearlet transform: a case study from the South Caspian Sea
Haleh Karbalaali 1 Abdolrahim Javaherian 1 2 5 Stephan Dahlke 3 Siyavash Torabi 4
+ Author Affiliations
- Author Affiliations
1 Department of Petroleum Engineering, Amirkabir University of Technology, Tehran 15857-4413, Iran.
2 Institute of Geophysics, University of Tehran, Tehran 14155-6466, Iran.
3 Department of Mathematics and Computer Sciences, Philipps Universität, Marburg 35032, Germany.
4 Seismic Data Processing Department, Dana Geophysics Company, Tehran 1919935331, Iran.
5 Corresponding author. Email: javaherian@aut.ac.ir
Exploration Geophysics 49(5) 704-712 https://doi.org/10.1071/EG17057
Submitted: 13 April 2017 Accepted: 2 October 2017 Published: 13 November 2017
Abstract
Channels are important sedimentary features in hydrocarbon plays either as targets for drilling or geohazards that should be avoided, depending on burial depth and fluid-fill. Either way, for well design purposes it is important to image channels before drilling. Shearlet transform, as a multi-scale and multi-directional transformation, is capable of detecting anisotropic singularities in two and higher dimensional data. In this study, the complex-valued shearlet-based edge measure was implemented for the aim of channel boundary detection. The method was applied to synthetic seismic time-slices containing channels with different signal-to-noise ratios as well as a real time-slice from the South Caspian Sea. The performance of the shearlet-based algorithm was compared both qualitatively and quantitatively with well known gradient-based edge detectors such as Sobel and Canny, resulting in successfully localising edges and detecting less false positives.
Key words: Canny operator, channel edge detection, complex shearlet-based edge measure, phase congruency, Sobel filter.
References
Al-Dossary, S., 2016, An efficient approach to simultaneous smoothing and edge detection: 86th Annual International Meeting, SEG, Expanded Abstracts, 3073–3077.Al-Dossary, S., and Marfurt, K. J., 2003, Improved 3-D seismic edge-detection filter applied to Vinton Dome, Louisiana: 73rd Annual International Meeting, SEG, Expanded Abstracts, 2370–2372.
Aqrawi, A. A., and Boe, T. H., 2011, Improved fault segmentation using a dip guided and modified 3D Sobel filter: 81st Annual International Meeting, SEG, Expanded Abstracts, 999–1003.
Aqrawi, A. A., Weinzierl, W., Daber, R., and Boe, T., 2012, Directional guided seismic attributes and their use in assisting structural, stratigraphic and lithological interpretation: 82nd Annual International Meeting, SEG, Expanded Abstracts, 1–5.
Bahorich, M., and Farmer, S., 1995, 3-D seismic discontinuity for faults and stratigraphic features: the coherence cube: The Leading Edge, 14, 1053–1058
| 3-D seismic discontinuity for faults and stratigraphic features: the coherence cube:Crossref | GoogleScholarGoogle Scholar |
Candes, E. J., and Donoho, D. L., 2005, Continuous curvelet transform: I. Resolution of the wavefront set: Applied and Computational Harmonic Analysis, 19, 162–197
| Continuous curvelet transform: I. Resolution of the wavefront set:Crossref | GoogleScholarGoogle Scholar |
Castagna, J., Sun, S., and Siegfried, R., 2003, Instantaneous spectral analysis: detection of low-frequency shadows associated with hydrocarbons: The Leading Edge, 22, 120–127
| Instantaneous spectral analysis: detection of low-frequency shadows associated with hydrocarbons:Crossref | GoogleScholarGoogle Scholar |
Chopra, S., and Marfurt, K. J., 2011, Structural curvature versus amplitude curvature: 81st Annual International Meeting, SEG, Expanded Abstracts, 980–984.
Chopra, S., and Marfurt, K. J., 2014, Observing fracture lineaments with Euler curvature: The Leading Edge, 33, 122–126
| Observing fracture lineaments with Euler curvature:Crossref | GoogleScholarGoogle Scholar |
Chopra, S., Kumar, R., and Marfurt, K. J., 2014, Seismic discontinuity attributes and Sobel filtering: 84th Annual International Meeting, SEG, Expanded Abstracts, 1624–1628.
Di, H., and Gao, D., 2014, Gray-level transformation and Canny edge detection for 3D seismic discontinuity enhancement: Computers and Geosciences, 72, 192–200
| Gray-level transformation and Canny edge detection for 3D seismic discontinuity enhancement:Crossref | GoogleScholarGoogle Scholar |
Do, M. N., and Vetterli, M., 2005, The contourlet transform: an efficient directional multi-resolution image representation: IEEE Transactions on Image Processing, 14, 2091–2106
| The contourlet transform: an efficient directional multi-resolution image representation:Crossref | GoogleScholarGoogle Scholar |
Fehmers, G. C., and Höcker, C. F. W., 2003, Fast structural interpretation with structure-oriented filtering: Geophysics, 68, 1286–1293
| Fast structural interpretation with structure-oriented filtering:Crossref | GoogleScholarGoogle Scholar |
Gersztenkorn, A., and Marfurt, K. J., 1999, Eigenstructure-based coherence computations as an aid to 3-D structural and stratigraphic mapping: Geophysics, 64, 1468–1479
| Eigenstructure-based coherence computations as an aid to 3-D structural and stratigraphic mapping:Crossref | GoogleScholarGoogle Scholar |
Karbalaali, H., Javaheran, A., Torabi, S., Dahlke, S., and Ghazanfari, A., 2017, Channel edge detection based on 2D compactly-supported shearlets: an application to a channelized seismic data in South Caspian Sea: 79th International Conference and Exhibition, EAGE, Expanded Abstracts, ThP405.
King, E. J., Reisenhofer, R., Kiefer, J., Lim, W.-Q., Li, Z., and Heygster, G., 2015, Shearlet-based edge detection: flame fronts and tidal flats: Applications of Digital Image Processing XXXVIII SPIE Conference Series, 9599, 1–11.
Kovesi, P., 1999, Image features from phase congruency: Videre: Journal of Computer Vision Research, 1, 1–26
Kovesi, P., 2000, Phase congruency: a low-level image invariant: Psychological Research, 64, 136–148
| Phase congruency: a low-level image invariant:Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD3M7hslGhtg%3D%3D&md5=054efc45e46a27609ba2d1ef3a2f667dCAS |
Kovesi, P., Richardson, B., Holden, E. J., and Shragge, J., 2012, Phase-based image analysis of 3D seismic data: 22nd International Geophysical Conference and Exhibition, ASEG, Expanded Abstracts, 1–4.
Ku, C.-Y., Lee, C.-P., and Lo, S.-Z., 2014, Identification of channel systems using coherence and spectral decomposition in offshore northwestern Australia: 84th Annual International Meeting, SEG, Expanded Abstracts, 2698–2702.
Kutyniok, G., and Labate, D., 2012, Shearlets: multiscale analysis for multivariate data: Springer Science Business Media.
Kutyniok, G., and Petersen, P., 2017, Classification of edges using compactly supported shearlets: Applied and Computational Harmonic Analysis, 42, 245–293
| Classification of edges using compactly supported shearlets:Crossref | GoogleScholarGoogle Scholar |
Labate, D., Lim, W. Q., Kutyniok, G., and Weiss, G., 2005, Sparse multidimensional representation using shearlets: SPIE Conference Series, 5914, 254–262.
Li, Y., Li, J., and Zheng, X., 2010, Channel system characterization using Wigner-Ville distribution-based spectral decomposition: 81st Annual International Meeting, SEG, Expanded Abstracts, 1418–1422.
Luo, Y., Higgs, W. G., and Kowalik, W. S., 1996, Edge detection and stratigraphic analysis using 3D seismic data: 66th Annual International Meeting, SEG, Expanded Abstracts, 324–327.
Luo, Y., Marhoon, M., Al-Dossary, S., and Alfaraj, M., 2002, Edge-preserving smoothing and applications: The Leading Edge, 21, 136–158
| Edge-preserving smoothing and applications:Crossref | GoogleScholarGoogle Scholar |
Marfurt, K. J., Kirlin, R. L., Farmer, S. L., and Bahorich, M. S., 1998, 3-D seismic attributes using a semblance-based coherency algorithm: Geophysics, 63, 1150–1165
| 3-D seismic attributes using a semblance-based coherency algorithm:Crossref | GoogleScholarGoogle Scholar |
Marfurt, K. J., Sadhaker, V., Gersztenkorn, A., Crawford, K. D., and Nissen, S. E., 1999, Coherency calculations in the presence of structural dip: Geophysics, 64, 104–111
| Coherency calculations in the presence of structural dip:Crossref | GoogleScholarGoogle Scholar |
Matos, M. C., and Marfurt, K. J., 2013, Subsurface geometry interpretation by integrating continuous wavelet transform seismic attributes: 13th International Congress of the Brazilian Geophysical Society & EXPOGEF, SBGF, Expanded Abstracts, 962–965.
Morrone, M. C., and Owens, R. A., 1987, Feature detection from local energy: Pattern Recognition Letters, 6, 303–313
| Feature detection from local energy:Crossref | GoogleScholarGoogle Scholar |
Morrone, M. C., Ross, J. R., Burr, D. C., and Owens, R. A., 1986, Mach bands are phase dependent: Nature, 324, 250–253
| Mach bands are phase dependent:Crossref | GoogleScholarGoogle Scholar |
Otsu, N., 1979, A threshold selection method from gray-level histograms: IEEE Transactions on Systems, Man, and Cybernetics, 9, 62–66
| A threshold selection method from gray-level histograms:Crossref | GoogleScholarGoogle Scholar |
Pampanelli, P. C. P., Mario Silva, P., and Gattass, M., 2013, A new volumetric fault attribute based on first order directional derivatives: 83rd Annual International Meeting, SEG, Expanded Abstracts, 1621–1625.
Partyka, G. A., Gridley, J., and Lopez, J., 1999, Interpretational applications of spectral decomposition in reservoir characterization: The Leading Edge, 18, 353–360
| Interpretational applications of spectral decomposition in reservoir characterization:Crossref | GoogleScholarGoogle Scholar |
Peyton, L., Bottjer, R., and Partyka, G., 1998, Interpretation of incised valleys using new 3-D seismic techniques: a case history using spectral decomposition and coherency: The Leading Edge, 17, 1294–1298
| Interpretation of incised valleys using new 3-D seismic techniques: a case history using spectral decomposition and coherency:Crossref | GoogleScholarGoogle Scholar |
Phillips, M., Fomel, S., and Swideman, R., 2016, Structure-oriented plane-wave Sobel filter for edge detection in seismic images: 86th Annual International Meeting, SEG, Expanded Abstracts, 1954–1959.
Reisenhofer, R., 2014, The complex shearlet transform and applications to image quality assessment: M.Sc. thesis, Technical University of Berlin.
Reisenhofer, R, Kiefer, J, and King, E. J., 2016, Shearlet-based detection of flame fronts: Experiments in Fluids, 57, 1–14
Rijks, E. J. H., and Jauffred, J. C. E. M., 1991, Attribute extraction: an important application in any detailed 3D interpretation study: The Leading Edge, 10, 11–19
| Attribute extraction: an important application in any detailed 3D interpretation study:Crossref | GoogleScholarGoogle Scholar |
Roberts, A., 2001, Curvature attributes and their application to 3D interpreted horizons: First Break, 19, 85–100
| Curvature attributes and their application to 3D interpreted horizons:Crossref | GoogleScholarGoogle Scholar |
Robinson, H., and Davis, T, 2012, Seismic reservoir characterization of distributary channel sandstones in the Lower Cretaceous Paluxy reservoir, Delhi Field, Louisiana: First Break, 30, 93–99
Russell, B., Hampson, D., and Joggel, L., 2010, Applying the phase congruency algorithm to seismic data slices: a carbonate case study: First Break, 28, 83–90
Saurez, Y., Marfurt, K. J., and Falk, M., 2008, Seismic attribute-assisted interpretation of channel geometries and infill lithology: a case study of Anadarko Basin Red Fork channel: 78th Annual International Meeting, SEG, Expanded Abstracts, 963–967.
Sinha, S., Routh, P. S., Anno, P. D., and Castagna, J. P., 2005, Spectral decomposition of seismic data with continuous wavelet transform: Geophysics, 70, P19–P25
| Spectral decomposition of seismic data with continuous wavelet transform:Crossref | GoogleScholarGoogle Scholar |
Song, J., Mu, X., Li, Z., Wang, C., and Sun, Y., 2012, A faults identification method using dip guided facet model edge detector: 82nd Annual International Meeting, SEG, Expanded Abstracts, 1–5.
Yi, S., Labate, D., Easley, R., and Krim, H., 2009, A shearlet approach to edge analysis and detection: IEEE Transactions on Image Processing, 18, 929–941
| A shearlet approach to edge analysis and detection:Crossref | GoogleScholarGoogle Scholar |