Seismic Edge Detection by Application of Cepstral Decomposition to Data Driven Modeled Geologic Channel Feature in Niger Delta

Orji O. M. (Department of Petroleum Engineering and Geoscience, Petroleum Training Institute, Effurun, Nigeria)
Ugwu S. A. (Department of Geology, University of Port Harcourt, Nigeria)
Ofuyah W. N. (Department of Earth Sciences, Federal University of Petroleum Resources, Effurun, Nigeria)

Abstract


Seismic edge detection algorithm unmasks blurred discontinuity in animage and its efficiency is dependent on the precession of the processingscheme adopted. Data-driven modeling is a fast machine learning schemeand a formal automatic version of the empirical approach in existence fora long time and which can be used in many different contexts. Here, a desired algorithm that can identify masked connection and correlation froma set of observations is built and used. Geologic models of hydrocarbonreservoirs facilitate enhanced visualization, volumetric calculation, wellplanning and prediction of migration path for fluid. In order to obtain newinsights and test the mappability of a geologic feature, spectral decomposition techniques i.e. Discrete Fourier Transform (DFT), etc and Cepstral decomposition techniques, i.e Complex Cepstral Transform (CCT), etc can be employed. Cepstral decomposition is a new approach that extends the widely used process of spectral decomposition which is rigorous when analyzing very subtle stratigraphic plays and fractured reservoirs. This paper presents the results of the application of DFT and CCT to a two dimensional, 50Hz low impedance Channel sand model, representing typical geologic environment around a prospective hydrocarbon zone largely trapped in various types of channel structures. While the DFT represents the frequency and phase spectra of a signal, assumes stationarity and highlights the average properties of its dominant portion, assuming analytical, the CCTrepresents the quefrency and saphe cepstra of a signal in quefrency domain.The transform filters the field data recorded in time domain, and recoverslost sub-seismic geologic information in quefrency domain by separatingsource and transmission path effects. Our algorithm is based on fast Fourier transform (FFT) techniques and the programming code was written within Matlab software. It was developed from first principles and outside oil industry’s interpretational platform using standard processing routines.The results of the algorithm, when implemented on both commercial andgeneral platforms, were comparable. The cepstral properties of the channelmodel indicate that cepstral attributes can be utilized as powerful tool inexploration problems to enhance visualization of small scale anomaliesand obtain reliable estimates of wavelet and stratigraphic parameters. Thepractical relevance of this investigation is illustrated by means of sampleresults of spectral and cepstral attribute plots and pseudo-sections of phaseand saphe constructed from the model data. The cepstral attributes revealmore details in terms of quefrency required for clearer imaging and betterinterpretation of subtle edges/discontinuities, sand-shale interbedding, differences in lithology. These positively impact on production as they serveas basis for the interpretation of similar geologic situations in field data.

Keywords


Complex Cepstral Transform ;Fourier transform ;Gamnitude ;Quefrency ;Saphe

Full Text:

PDF

References


[1] Satinder, C., Marfurt, K. J., Misra, S. Seismic Attributes on Frequency-Enhanced Seismic Data; Recovery, 2011

[2] Ofuyah, W.N.,Alao,O.A., Olorunniwo, M.A. The Application of Complex Seismic Attributes in Thin Bed Reservoir Analysis,Journal of Environment and Earth Science, 2014, 4(18): 1-12

[3] Hall, M. Predicting Stratigraphy with Cepstral decomposition. The leading Edge 25 (2), February (Special issue on spectral decomposition), 2006. DOI: 10.1190/1.2172313

[4] Tuttle, Michele. Charpentier, Ronald; Brownfield, Michael. The Niger Delta Petroleum System: Niger Delta Province, Nigeria, Cameroon, and Equatorial Guinea, Africa. United States Geologic Survey. United States Geologic Survey, 2015.

[5] Avbovbo, A. A. Tertiary lithostratigraphy of Niger Delta. American Association of Association of Petroleum Geologists, Tulsa, Oklahoma, 1978: 96-200.

[6] Merki, P. J. Structural Geology of the Cenozoic Niger Delta. In: Dessauvagie, T. F. J. and Whiteman, A. J. (eds), African Geology, University of Ibadan Press, Nigeria. 1972: 635-646.

[7] Weber, K. J. Hydrocarbon Distribution patterns in Nigeria Growth Fault Structure Controlled by Structural Style and Stratigraphy, Journal of Petroleum Sciences and Engineering, 1987, 1: 91-104.

[8] Merki, P. J. Structural Geology of the Cenozoic Niger Delta. In: Dessauvagie, T. F. J. and Whiteman, A. J. (eds), African Geology, University of Ibadan Press, Nigeria. 1972: 635-646.

[9] Corredor, F., Shaw, J. H., Bilotti, F. Structural styles in the deepwater fold and thrust belts of the Niger Delta: American Association of Petroleum Geologist Bulletin, 2005, 89(6): 753-780.

[10] Taner, M.T.K, Koehler, F., Sheriff, R.F. Complex seismic trace analysis. Geophysics, 1979, 44(6): 1041-1063.

[11] Yilmaz, O. Seismic data processing, Oklahoma. Society of Exploration Geophysics, 2001, I and II: 1-2024

[12] Hall, M. Predicting Stratigraphy with Cepstral decomposition. The leading Edge 25 (2), February (Special issue on spectral decomposition), 2006. DOI: 10.1190/1.2172313

[13] Jeong, J. Kepstrum Analysis and Real-Time Application to Noise Cancellation, Proceedings of the 8th WSEAS International Conference on Signal Processing, Robotics and Automation. 2009: 149-154. ISSN: 1790, ISBN: 978-960-474-054-3

[14] Bogert,B.P. Healy, M. J. R., Tukey,: J. W. The Quefrency Alanysis [sic] of Time Series for Echoes: Cepstrum, Pseudo Autocovariance, Cross-Cepstrum and Saphe Cracking. Proceedings of the Symposium on Time Series Analysis (M. Rosenblatt, Ed). New York: Wiley, 1963, 14: 209-243.

[15] Oppenheim,A.V. Superposition in a Class of Nonlinear Systems" Ph.D. diss., Res. Lab. Electronics, M.I.T, 1965.

[16] Hall, M. Predicting Stratigraphy with Cepstral decomposition. The leading Edge 25 (2), February (Special issue on spectral decomposition), 2006. DOI: 10.1190/1.2172313

[17] Oppenheim, A.V., Schafer, R. W. Homomorphic Analysis of Speech. IEEE Trans. Audio Electro acoust, Vol. AU-16, pp. 221-226, R.W. Schafer, Echo Removal by Discrete Generalized Linear Filtering:Res. Lab. Electron.MIT,Tech. Rep., 1969, 466.

[18] Silvia, M.T., Robinson, E.A 1978. Use of the Kepstrum in Signal Analysis. Geoexploration, 1978, 16(1-2): 55-73.

[19] Hall, M. Predicting Stratigraphy with Cepstral decomposition. The leading Edge 25 (2), February (Special issue on spectral decomposition), 2006. DOI: 10.1190/1.2172313

[20] Satinder, C., Marfurt, K. J., Misra, S. Seismic Attributes on Frequency-Enhanced Seismic Data. Recovery, 2011

[21] Reza Mohebian, Mohammad Ali Riahi, Omid Yousefi. Detection of channel by seismic texture analysis using Grey Level Co-occurrence Matrix based attributes. Journal of Geophysics and Engineering. 2018, 15: 1953-1962. https://doi.org/10.1088/1742-2140/aac099

[22] Jenkins, G.M., Watts. D.G. Spectral analysis and its applications, Published by Boca Raton, Fl.: Emerson-Adams Press, 1968: 525. http://trove.nla.gov.au/version/39694417

[23] Subramanyam,D., Rao, P.H. Seismic Attributes: A Review, 7th, International Conference & Exposition on Petroleum. Geophysics, Hyderabad, 2008: 398-404



DOI: https://doi.org/10.30564/jgr.v2i2.2046

Refbacks

  • There are currently no refbacks.
Copyright © 2020 Orji O. M., Ugwu S. A., Ofuyah W. N.


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.